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AI and the future of work income and inequality

Mon, 09 Nov 2026 10:19:30 +0000

AI could allow society to produce more with less human labour. Whether that translates into more leisure, greater insecurity or a wider gap between rich and poor will depend on how income, ownership and public services change alongside it.

Imagine a business that can deliver the same service with half the human effort. Its owners could reduce prices, increase profits, serve more customers, improve pay or shorten the working week. They could also reduce the number of people they employ.

All of those outcomes begin with the same technological improvement. Their consequences for the people involved are very different.

That is the difficulty at the centre of the debate about AI and the future of work. We can imagine machines doing a growing share of economically valuable activity. It is much harder to explain how everyone will live comfortably if paid employment becomes less necessary.

For most households, work provides the money that buys access to housing, food, energy and everything else. A future in which society needs less labour would therefore require more than better technology. It could require a different relationship between work and the right to a decent standard of living.

There is no reliable date for that future, and no certainty that it will arrive in its most dramatic form. But exploring it helps explain the decisions already facing businesses and governments.

What the evidence tells us about jobs

The claim that AI will eliminate most employment goes much further than the research can currently establish.

The International Labour Organization and NASK estimated in May 2025 that one in four jobs worldwide was in an occupation potentially exposed to generative AI. Their assessment said that changes to jobs were more likely than their complete replacement. Exposure measures the potential for technology to affect tasks; it does not count redundancies or predict how quickly employers will adopt it.

A job usually combines many activities. Producing a report, handling an unusual complaint, taking responsibility for a decision and understanding what a customer actually needs may sit within the same role. Automating one activity does not automatically remove the rest.

There is also evidence that AI can help people work more effectively. A study published in The Quarterly Journal of Economics in 2025 examined 5,172 customer-support agents and found that access to an AI assistant increased issues resolved per hour by 15% on average. Less experienced and lower-skilled workers gained more than their more experienced colleagues. That is evidence from a particular workplace, rather than a prediction for the whole economy.

These findings leave room for several outcomes. Employers might expand services with the same team, employ fewer people, or combine both approaches. Productivity improvements do not determine which choice they make.

Software capability also differs from economical, dependable deployment. Systems need to work with existing processes, handle mistakes and justify their operating costs. Extending automation into construction, maintenance or personal care introduces physical challenges that a more capable chatbot alone does not solve.

Why a richer economy might still leave households worse off

The most important distinction is between producing wealth and distributing purchasing power.

Suppose a fictional company earns £1 million a year and spends £600,000 on wages. Imagine that automation eventually allows it to maintain its output while reducing that wage bill to £300,000. Assume, purely for illustration, that the technology and its operation add £100,000 in annual costs.

The business would then have £200,000 more available before any other changes. That money could support investment, lower prices, higher pay, shorter hours or greater returns to owners. The £300,000 reduction in wages could involve fewer staff, reduced hours or another change in employment.

This example is arithmetic, not a forecast. It shows why a more productive business does not automatically make every affected household better off.

Consumers might gain through lower prices while some workers lose their main source of income. Investors might benefit through higher profits while people without savings have little direct claim on those returns. The economy could grow overall while particular communities become poorer.

The IMF has identified both labour-income and ownership channels through which AI could increase inequality: some workers may benefit more than others, while higher returns to capital could favour people who already own assets. These are risks, rather than an unavoidable outcome.

The distribution of productivity gains can follow several routes:

Four possible futures for work

There is no single economic theory that tells us precisely what comes next. Four broad scenarios help explain the range of possibilities.

Possible future	How people earn a living	What could happen to inequality
AI assists most workers	Wages remain central, with jobs changing around AI	Gaps could narrow where tools spread expertise, or widen where access and bargaining power differ
Productivity supports shorter working weeks	People retain paid work but share some gains through more free time	Benefits depend on whether lower hours preserve adequate income and extend beyond privileged occupations
Ownership becomes more important than employment	Profits, assets and access to platforms matter more, while wages become less secure	Wealth could concentrate if displaced workers have little ownership or protection
Much less paid work is needed	Income comes from a mixture of remaining jobs, public transfers, services and ownership returns	Living standards depend heavily on who controls production and how its benefits are shared

These scenarios could coexist. A consultant might become more productive, an administrator might lose a role, a care worker might remain in high demand and a shareholder might receive higher returns during the same period.

The path between them matters as much as the eventual destination. A society that becomes wealthier over twenty years can still impose severe losses on people who cannot pay their bills during the transition.

How people could live if there were less paid work

If employment became a less reliable way to distribute income, households would need other sources of security. Several approaches could contribute, but each answers a different part of the problem.

Shorter working weeks

One possibility is to distribute some productivity gains as time. If a team can complete its work in fewer hours, an employer could preserve pay while reducing working time. People would still earn wages, but employment would occupy less of their lives.

This is different from cutting someone's hours and income because there is less work available. A shorter working week only represents a shared benefit if households can still afford to live.

It would also be harder to deliver evenly across occupations. Reducing office administration may free time directly; maintaining round-the-clock physical care still requires people to cover shifts unless technology changes the underlying work.

Shorter hours are therefore a possible route towards sharing gains, rather than an automatic consequence of AI adoption.

A guaranteed income

Universal basic income, usually shortened to UBI, would provide a regular payment to everyone within an eligible population without making it conditional on employment.

Its appeal is straightforward: people would retain a financial floor even when their work disappeared, their hours varied or they needed time to retrain. Other designs, such as a guaranteed minimum income, would target support more closely according to income.

But the amount and funding matter enormously. A modest payment might improve security without being sufficient to replace wages. A payment large enough to support most living costs would require a much more substantial funding arrangement.

For scale, an illustrative payment of £1,000 a month to 50 million adults would have a gross annual cost of £600 billion. That is not a proposal or a net budget estimate. Taxes paid back by recipients and any benefits replaced would change the net cost, while protecting disability, housing and other additional needs would affect the design.

Finland's 2017 to 2018 basic-income experiment found better reported wellbeing and economic security, alongside small employment effects whose interpretation was complicated by another policy change. It provides useful evidence about a limited trial among unemployed people, rather than proof that a permanent national scheme could support a highly automated economy.

A credible income proposal must also explain what happens to essential costs. If housing supply remains constrained, additional purchasing power could partly feed into higher rents. That is a reason to consider income and housing together, rather than assume that a cash payment alone resolves insecurity.

Better access to essential services

Households can become more secure through a lower cost of living as well as a higher cash income.

Affordable housing, transport, education, childcare and reliable public services could reduce the amount people need to earn privately. AI might help provide some services more efficiently, although translating administrative savings into better provision would still require investment and competent delivery.

This approach is often discussed as universal basic services. Its practical question is whether people can obtain what they need, rather than simply whether they have received a payment.

Cash and services need not be competing choices. A future with less paid work could require both personal spending power and dependable access to essentials.

A wider share of ownership

Redistribution after profits have been earned is only one way to share the benefits. Another is to spread ownership of the assets generating them.

Employee ownership, profit-sharing, pension investment and publicly owned investment funds are possible mechanisms. A public fund could, in principle, hold investments and use returns to support services or payments to citizens.

None offers free or guaranteed income. Funds need assets, returns fluctuate and governance matters. Employee shares also expose workers to the fortunes of their own employer, which can compound risk if both their job and investment lose value together.

The underlying principle is still relevant: if a greater share of income comes from owning productive assets, access to ownership becomes more important to economic security.

Who would pay for a society with less work

A more automated economy would still have to produce the homes, food, energy and services that people consume. Money transfers cannot replace that productive capacity.

If AI expanded output substantially, society might have more resources available to share. The challenge would be creating institutions that convert that capacity into household security.

Public funding could come from a mixture of taxes, investment returns and changes to existing expenditure. If wages became a smaller share of economic income, governments might need to reconsider how heavily revenue collection depended on employment.

The IMF's 2024 discussion of fiscal responses to AI recommended stronger social protection and consideration of capital-income and corporate taxation. It also cautioned against a specific tax on AI itself, citing risks to investment and difficulties with implementation.

There is no simple answer in taxing every automated task. Governments would need to distinguish productive investment from excessive concentration of economic power, collect revenue effectively and avoid undermining the growth expected to fund better living standards.

International coordination would matter where profits and productive assets crossed borders. A country could experience disruption to local employment without automatically receiving a proportionate share of the gains.

Business incentives would remain important too. Companies need customers with purchasing power, but that does not mean each company has an incentive to preserve employment on society's behalf. A business can cut its own wage bill while relying on customers who earn money elsewhere. Wider economic security therefore cannot depend solely on voluntary decisions by individual employers.

Why cheaper intelligence would not make everything cheap

A common vision of the AI future assumes that dramatically cheaper intellectual work will make life broadly affordable. That could happen in some areas without happening everywhere.

Producing another digital document or software feature is different from supplying another home in a desirable location. Land, building materials, energy networks, physical infrastructure and human attention can remain scarce.

AI could help improve planning, design, logistics or research. Those improvements would not automatically create the physical capacity or political agreement needed to increase supply.

A household might gain access to excellent low-cost software while still struggling with rent. A business might generate marketing material cheaply while paying heavily for distribution, premises or access to customers.

Affordability would depend on which costs fell, whether competition passed savings through, and whether the essentials occupying household budgets became easier to obtain. A comfortable life requires more than abundant digital output.

How inequality could change

AI could affect several kinds of inequality at once, sometimes in opposing directions.

Within a workplace, accessible tools might help less experienced people perform tasks that previously required substantial training. The customer-support study offers one example of that possibility. It does not establish that wages will converge, because pay also depends on labour demand, institutions and bargaining power.

Between households, the effects could move in the opposite direction. Someone with a home, investments and a secure professional position may have several ways to benefit from automation. Someone relying entirely on a vulnerable wage may have much less protection.

The result could be a smaller gap in certain skills alongside a larger gap in wealth and security.

There is also a question of market power. In April 2024, the UK's Competition and Markets Authority warned that control of important inputs and routes to market could allow powerful technology firms to restrict competition in foundation-model markets. Its concern was that businesses and consumers could lose out through reduced choice, higher prices or weaker innovation.

For smaller businesses, that creates an unresolved tension. AI could make capabilities affordable that previously required a large team. It could also increase dependence on suppliers that control models, infrastructure or customer access. Whether small firms gain lasting bargaining power would depend partly on how open and competitive those markets remain.

Geography matters as well. Lower-cost access to expertise could benefit people far from major economic centres. But a community losing a significant source of employment would not necessarily recover just because useful software became available.

Access to tools is one part of opportunity. Time, education, infrastructure, capital and a realistic route to earning income are others.

The transition could be harder than the eventual future

Even if AI ultimately supports higher living standards, the adjustment could be painful.

A person losing a job needs income immediately. Training takes time, available vacancies may be elsewhere, and a new occupation may offer lower pay. “Reskilling” only becomes a meaningful answer when there is accessible training, financial support and work worth moving into.

The transition could also affect how people enter professions. If businesses automate activities traditionally assigned to junior staff, they would need alternative ways to develop experienced employees. That is a risk to plan for, rather than proof that every entry-level role will disappear.

For employers, useful questions include how productivity gains will be shared, how staff will learn, and where human judgement remains necessary. Measuring only output or headcount would miss changes in service quality, workload and the development of future expertise.

For governments, the equivalent questions concern income support, housing, training and the speed at which assistance reaches affected communities. An eventual increase in national output would offer little comfort to someone facing several years of financial instability.

What people would do if employment occupied less of life

Paid work provides more than money. For many people it offers routine, relationships, recognition and a sense of contribution. A future with less employment would need to take those roles seriously.

But useful activity extends well beyond paid jobs. Raising children, caring for relatives, supporting charities, creating art, learning and participating in local communities can all have considerable value without generating a wage.

Greater financial security and more free time could allow more of that activity. It could also allow people to start businesses or pursue projects that cannot immediately support them.

The experience would depend heavily on choice. Working fewer hours with a secure income is very different from being excluded from employment while struggling to afford essentials. Describing both situations as “people not working” hides the most important difference between them.

A successful future would need room for contribution without treating conventional employment as the only measure of a person's worth. It would also need to recognise that preferences differ: some people would welcome more leisure, while others would continue to seek demanding paid work.

The future depends on how the gains are shared

There is a credible possibility that AI will help people accomplish far more with less effort. There is much less certainty about whether it will remove the need for most paid employment, how quickly any transition would happen, or which occupations would be affected most.

The sensible response is to prepare for several outcomes. Businesses can use AI to improve services and productivity while making deliberate choices about staff development, workload and the distribution of gains. Governments can strengthen the systems that help people navigate changes in employment, while considering how income and ownership might evolve if those changes become more profound.

The most optimistic future would combine productive technology with economic security and greater freedom over how people spend their lives. A less favourable one would combine impressive output with concentrated ownership, fragile incomes and limited influence over the systems on which people depend.

The technology could contribute to either. Whether people can live well with less paid work will depend on the arrangements built around it: who owns productive assets, how markets operate, which essentials are affordable, and how people obtain a fair share of what society produces.

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AI Agents and the Future of Business Software

Thu, 08 Oct 2026 09:00:00 +0000

Businesses have spent years investing in software to make work easier, yet a considerable part of the working day still involves operating that software. Employees search for records, update fields, move information between applications and work out which screen contains the answer they need. Even when each application is reasonably good, the person using it often becomes responsible for joining everything together.

We think this is likely to change substantially. Our expectation is that AI agents will become the primary way people interact with software for many routine business tasks. Employees will describe what they want to achieve, while agents retrieve information, use the appropriate tools and carry out work across the systems underneath.

That future will develop unevenly, and there are good reasons for people to retain direct control over certain tasks. Nevertheless, it has practical implications for businesses today. The quality of your data, the structure of your processes and the accessibility of your applications could soon have a much greater influence on how effectively your team works.

From navigating applications to asking for outcomes

Consider what happens when an account manager needs to prepare for a customer meeting. They might open the CRM to review recent conversations, check the accounting system for outstanding invoices, look through support tickets and visit the project management platform to understand how ongoing work is progressing.

The information is already available, but gathering it requires the employee to know where to look and how to interpret what they find. A straightforward request becomes a small research exercise across several applications.

An agent with suitable access could potentially assemble that information from a single instruction:

“Prepare me for tomorrow’s meeting with this customer. Summarise recent activity, outstanding issues and anything we need to discuss.”

The more significant opportunity comes afterwards. Having reviewed the summary, the employee could ask the agent to prepare an agenda, create an internal follow-up task or draft a message to the project manager. With the appropriate tools and permissions, the agent could carry out those actions in the relevant systems.

AI systems can already be designed to use tools and choose steps towards an objective. Anthropic’s guidance on building effective agents describes this distinction between predefined workflows and agents that determine how to proceed as they work. That capability provides a foundation for the change we expect, although dependable business use still requires careful implementation. anthropic.com

The employee’s attention can then move towards the customer and the decisions that need making, with less time spent navigating software to gather the necessary context.

Software becomes the infrastructure behind the work

If agents become the main point of interaction, the applications underneath them will continue to perform essential functions. Accounting software will maintain financial records, the CRM will organise customer relationships, and project management systems will hold tasks, responsibilities and deadlines.

What changes is how often an employee needs to open each application directly.

We can imagine a working day in which someone reviews priorities through an assistant, asks it to investigate an issue and approves a proposed action without visiting every system involved. Some tasks may begin through a conversation, while others start automatically when an agreed condition is met.

A renewal process, for example, could bring together contract dates, current services, account activity and outstanding issues before presenting a proposed renewal for review. The person responsible would still make the commercial decision, but much of the preparation could happen in the background.

This would also change what businesses value when choosing software. The interface would remain relevant, but buyers would have stronger reasons to examine the capabilities underneath it: whether information can be retrieved reliably, whether actions can be performed through integrations, and whether access can be restricted appropriately.

A feature that is available only through a sequence of manual screens may be much harder to incorporate into an agent-led process.

Interfaces will still have a role

We expect businesses to spend less time navigating application interfaces, but that does not mean every task should become a conversation.

A table can be a better way to compare hundreds of records. A project board can make workload easier to understand. A chart can reveal a trend more clearly than several paragraphs of explanation. People will also need ways to inspect evidence, review proposed changes and investigate mistakes.

The likely direction is a combination of agents and interfaces, with the agent bringing forward the view needed for a particular decision. Someone might ask which projects are falling behind and receive an interactive table showing deadlines, blockers and responsible team members. They could examine the details before asking for follow-up actions.

In that environment, interfaces become more focused on helping people understand and control the work. Routine navigation and administration can increasingly happen behind the scenes.

Why MCP matters to this future

For agents to work across business applications, they need a reliable way to access information and perform actions. Model Context Protocol, or MCP, provides an open standard for connecting AI applications to external tools and data sources. An MCP server can expose specific capabilities that a compatible AI application can discover and use. Model Context Protocol

We explored the underlying technology in our earlier article, What is MCP, and what does it mean for businesses?. Its relevance here is that a common connection standard can make business systems more accessible to agents.

For example, a connection might expose tools for finding customer records, retrieving invoice information or creating tasks. The agent can request those operations using defined inputs, while the connected system performs the underlying action. The actual capabilities depend on what the integration makes available. Model Context Protocol

Businesses should therefore look beyond whether a supplier says it “supports MCP”. A connection that retrieves a small selection of information offers a different opportunity from one that supports the complete process you want to improve.

It is also worth examining existing APIs and integration options. MCP often provides an additional layer over those capabilities, so the accessibility of the underlying application remains important. Businesses can start evaluating these foundations now without committing themselves to a particular agent platform.

Good data hygiene becomes an operational requirement

An employee can often work around poor data because they know the business. They recognise that two slightly different company names refer to the same customer, understand which spreadsheet is current and remember that a supposedly active contract ended last month.

An agent may have no dependable way to resolve those inconsistencies. If it finds two customer records with different renewal dates, it needs an authoritative source or a defined process for handling the conflict.

This makes good data hygiene particularly important when AI moves from producing answers to performing actions. An incorrect email address might lead to a message being sent to the wrong person. An outdated service record could affect a renewal proposal. An ambiguous account status could trigger an inappropriate follow-up.

Preparing data for agents therefore involves more than removing duplicates. Businesses need consistent fields, meaningful statuses, clear relationships between records and an agreed source of truth for each important type of information.

Customer identities should be linked reliably across systems. Dates and currencies should be explicit. Superseded documents should be distinguishable from current ones. Important decisions should be recorded somewhere accessible rather than remaining entirely in someone’s inbox or memory.

These improvements benefit people immediately. They also make it easier to introduce automation with confidence because there is less ambiguity for either an employee or an agent to interpret.

How businesses can get ahead now

The strongest starting point is a specific piece of work that repeatedly consumes time. Meeting preparation, internal reporting and finding information across applications are useful candidates because the results can be checked before the agent is given permission to change anything.

We would approach preparation in five stages:

Stage	Practical action
Identify the work	Choose a recurring task with a clear outcome and record how much time it currently takes.
Improve the data	Resolve duplicates, standardise key fields and agree which system holds each authoritative record.
Check connectivity	Assess relevant APIs, MCP connections, available actions and permission controls.
Define responsibility	Decide what the agent can do independently and when a person needs to review or approve it.
Test and measure	Compare results with the existing process, including errors, checking time and integration costs.

Access should follow the needs of the task. An agent preparing an account summary may need permission to read selected information, while an agent updating customer records requires a different level of control. MCP documentation describes mechanisms such as tool availability settings, approval dialogues and activity logs, but businesses still need to implement and configure suitable controls. Model Context Protocol

Testing should include the awkward cases: missing information, conflicting records, unavailable applications and requests the agent is not authorised to complete. A useful system needs to recognise those situations and make them visible.

The measure of success is the improvement to the complete process, including the time people spend checking the agent’s work. A task completed quickly has limited value if it creates a larger verification burden afterwards.

Processes need to be clear enough to delegate

Clean data alone will not explain how your business should operate.

An instruction such as “follow up overdue customers” sounds simple until someone needs to decide what counts as overdue, whether disputed invoices are excluded, who owns the relationship and which customers require a more sensitive approach.

Employees often learn these rules informally. Delegating the work to an agent requires the business to make them explicit.

That means defining the intended outcome, the information required, the actions allowed and the situations that need human judgement. It also means accepting that some parts of a process are better handled by conventional automation. A fixed calculation or validation rule can remain in software, while an agent helps gather context or manage a less predictable sequence of tasks.

For many businesses, documenting those boundaries will be one of the most useful parts of preparing for agents. It exposes assumptions and inconsistencies that may already be causing problems.

Our view

We think agents are likely to become the main way people use business software for a substantial amount of everyday work. The pace will vary, but the opportunity is clear: people can spend more time deciding, communicating and delivering, while software takes on more of the effort involved in finding information and carrying out routine actions.

Businesses can prepare without predicting which AI provider or protocol will dominate. Well-structured data, accessible applications, documented processes and sensible permissions are useful foundations across a wide range of possible futures.

The organisations that make progress on those foundations now will have more opportunities to put agents to useful work as the technology develops. They will also have better systems for their teams in the meantime.

If you want to understand where agents could help your business, Ostratto can help you review the systems and processes you already have, identify a practical starting point and put the right foundations in place.

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Get in touch with the team to discuss how we support your business with practical, people-first technology and long-term solutions.

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Learn who we are, what we stand for, and how Ostratto helps businesses make their work, less work through practical technology solutions.

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Google Workspace Studio gets new security controls: what SMEs need to know

Tue, 25 Aug 2026 09:44:00 +0000

AI at work is moving beyond drafting an email or summarising a meeting. The next step is software that can send a message, update a file, move information between systems or trigger a process for you.

That can remove useful amounts of admin. It also changes the risk. A poor answer from an assistant is inconvenient; a poorly governed automation can share the wrong information, change a record or keep running after the process around it has changed.

On 17 August, Google announced new security and governance controls for Workspace Studio, its no-code tool for building agentic workflows within Google Workspace. The important business question is no longer only “What can we automate?” It is “How do we automate without losing control?”

What is changing?

Workspace Studio originally focused more on helping a user with a task, such as drafting an email. Google is now introducing more cross-user collaboration actions, alongside controls for identity, access, auditing, human approval and data protection.

For newly created flows, Google says the automation will run with the user’s identity but receive only the privileges needed for the flow. It can also receive a unique, auditable identity, so an administrator can distinguish the flow from its owner when reviewing activity.

That is a useful improvement, but it does not repair untidy access permissions. Google’s administration guidance says a newly created flow can, by default, read, modify and share the same Workspace data its creator can access. If that person can see too much, the automation may still inherit a wider data footprint than the process needs.

Administrators are also getting an Agent access management view. It can show new Studio flows, pause their access to Google data or restrict particular access scopes. Audit events can include the flow identifier and owner context, while additional settings can disable certain steps, Gemini data access or webhook integrations.

Human approval is part of the control model

Not every automated action should complete without a person checking it. Google now allows administrators to require approval when a flow affects people outside the organisation, such as adding content to an externally shared file or messaging an external group.

That is a sensible default around customer communications, personal information, contractual commitments and anything involving money or access rights. The flow can prepare the next action, but accountability stays with a person before information leaves the organisation.

The approval control is supported on Business Starter, Business Standard and Business Plus, as well as specified Enterprise and Education editions. More advanced data loss prevention controls for Studio and Gemini have a narrower edition list, including specified Frontline, Enterprise, Education and Enterprise Essentials plans. Do not assume every security control arrives with every Workspace subscription.

The rollout has important limits

Google began rolling out the administration settings to Rapid and Scheduled Release domains on 17 August. Rapid Release end-user features started on 20 August, while broader Scheduled Release end-user features are due to begin on 1 September. Identity attribution is still labelled beta; its Scheduled Release rollout is due to start on 24 August.

Availability will therefore vary by tenant and release track. More importantly, the first wave of least-privileged identity, identity attribution, richer audit context and Agent access management applies to newly created flows. Google says support for existing flows will come later.

That creates a practical review point. An organisation with older flows should not assume the new dashboard and identity model cover them simply because the administration controls appear in the console.

What should SMEs do now?

Start with one bounded process. Choose a repetitive task with clear rules, a visible outcome and an easy way to reverse mistakes. Creating a standard project folder and notifying the delivery team is a better pilot than allowing an agent to decide what happens across an entire customer journey.
Map data and permissions first. Record what the flow needs to read, what it can change, who owns it and what it must never access. Review the creator’s underlying Drive, Gmail and group permissions before relying on the phrase “least privilege”.
Keep approval around consequential actions. Require a person before external sharing, payments, personal-data handling, access changes or contractual communication. Automation should remove friction, not accountability.
Separate new and existing flows. Build an inventory with owner, purpose, data access, release date and review date. Confirm which flows appear in Agent access management and which still operate under the older model.
Review flows like user accounts. Recheck them when an owner changes role, a process changes or the data becomes more sensitive. Pause or retire flows that no longer have a clear business owner.

For an example of how centrally managed, auditable Google Workspace can support everyday operations, see our case study with a global B2B marketing business.

Our view

This is more consequential than another AI writing feature. As we discussed in our practical AI predictions for small businesses, the value of agents will come from helping real work move forward, but the more an agent can do, the more identity, permissions, logging and human approval matter.

Google’s controls are a useful step towards that balance. They provide better visibility and a more credible way to limit action, but the rollout is not complete, older flows are not yet fully covered and advanced data protection remains edition-specific. Doing nothing for a week or two is reasonable if your tenant, ownership model or permissions are not ready.

For most SMEs, the right move is a small, measurable pilot with clear boundaries. Automate one high-friction process, watch what the flow can access and keep a person responsible for the result.

If you are exploring Google Workspace automation, Ostratto can help you map the workflow, permissions and controls before you switch it on. Talk to us about Google Workspace.

Contact

Get in touch with the team to discuss how we support your business with practical, people-first technology and long-term solutions.

About

Learn who we are, what we stand for, and how Ostratto helps businesses make their work, less work through practical technology solutions.

Learn More

Our Approach

Discover how we partner with you - focusing on strategy, simplicity and long-term value to deliver technology that truly supports your business.

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What's BIMI - and should your business be using it?

Fri, 23 Jan 2026 14:14:50 +0000

Email security has come a long way in recent years. Most businesses are now familiar with SPF, DKIM and DMARC as the foundations of protecting their domain from spoofing and phishing. But there’s a newer standard gaining attention: BIMI.

BIMI promises better brand recognition, improved trust, and a visual stamp of authenticity in your customers’ inboxes. Sounds great… but is it actually realistic for small businesses right now?

Let’s break it down.

What is BIMI?

BIMI (Brand Indicators for Message Identification) allows your organisation’s logo to appear next to emails you send in supported inboxes (such as Gmail and Yahoo).

Instead of just seeing a sender name or generic initial, recipients can see your verified brand logo alongside your email. This helps users quickly recognise legitimate messages and reduces the risk of phishing.

In short:

Stronger brand visibility
Increased trust with recipients
Clearer separation from spoofed or fraudulent emails

But BIMI isn’t just a logo upload. It’s tightly linked to email authentication and security standards.

Without BIMI

With BIMI

The Prerequisites for BIMI

Before BIMI is even an option, your email domain must meet strict security requirements:

So far, all reasonable… until we get to the biggest barrier.

1. DMARC enforcement

Your domain must have DMARC set to p="quarantine" or p="reject.

This means:

SPF and DKIM must be correctly configured
You must be confident that legitimate mail won’t be blocked
Any unauthorised senders are actively rejected or quarantined

You can read more about DMARC here.

2. A compliant BIMI logo

Your logo must be:

In SVG Tiny 1.2 format
Square and properly optimised
Hosted securely and publicly accessible

This isn’t a standard SVG export and often requires specialist design or conversion work.

3. A BIMI DNS record

A DNS record is added to your domain that:

Points to your logo
References your Verified Mark Certificate (VMC)

So far, all reasonable… until we get to the biggest barrier.

The Blocker: Verified Mark Certificates (VMCs)

To display a BIMI logo in major inboxes like Gmail, you need a Verified Mark Certificate.

A VMC:

Proves you own the logo
Confirms you have the legal right to use it
Is issued by a recognised Certificate Authority (such as DigiCert)

Why this is a problem for small businesses

VMCs come with two major costs:

Trademark registration - Your logo must be a registered trademark. This alone can cost hundreds to thousands of pounds and take months to complete.
Annual certificate fees - VMCs typically cost £800–£1,500+ per year, depending on the provider.

For large brands, this is a reasonable investment.

For most small businesses, it simply isn’t.

Is BIMI worth it right now?

For enterprise organisations and well-known brands, BIMI makes sense:

They already have trademarks
The cost is marginal relative to marketing budgets
Brand impersonation is a serious risk

For small and growing businesses, the reality is different.

While BIMI is technically impressive, it’s currently:

Expensive to implement
Dependent on trademark ownership
Limited in inbox support
Hard to justify compared to other security improvements

Right now, BIMI is more of a “nice to have” than a necessity for most SMEs.

What should small businesses focus on instead?

If your goal is email trust and security, your effort is usually better spent on:

Properly configured SPF, DKIM and DMARC
Gradually moving DMARC to enforcement (quarantine → reject)
Monitoring DMARC reports to prevent legitimate mail issues
Reducing spoofing and phishing risks at the domain level

These steps deliver real security benefits without the high costs attached to BIMI.

Our View

BIMI is a great idea, but it’s not yet accessible for most small businesses.

As the ecosystem matures and costs come down, we expect BIMI to become far more achievable. Until then, getting your email authentication right is the most effective way to protect your brand and your customers.

If you’re unsure where your domain stands - or want help tightening up your email security - we can help you get there, without unnecessary complexity or expense.

Contact

Get in touch with the team to discuss how we support your business with practical, people-first technology and long-term solutions.

About

Learn who we are, what we stand for, and how Ostratto helps businesses make their work, less work through practical technology solutions.

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Our Approach

Discover how we partner with you - focusing on strategy, simplicity and long-term value to deliver technology that truly supports your business.

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DMARC: What's going on?

Wed, 26 Feb 2025 10:54:36 +0000

Email security is a critical component of any organisation's cybersecurity strategy. Yet, despite its importance, many businesses have been slow to adopt DMARC (Domain-based Message Authentication, Reporting & Conformance). DMARC helps prevent email spoofing, phishing, and other cyber threats, but its implementation has lagged behind.

In this article, we'll explore why DMARC adoption has been slow and provide a step-by-step guide on how to set it up for your domain.

What is DMARC?

DMARC is an email authentication protocol designed to protect domains from being used for email spoofing and phishing attacks. It works by ensuring that emails sent from your domain are properly authenticated using SPF (Sender Policy Framework) and DKIM (DomainKeys Identified Mail).

A DMARC policy tells receiving mail servers what to do when an email fails authentication—whether to monitor (no action), quarantine (send to spam), or reject (block outright) unauthorised emails.

How DMARC Works

SPF and DKIM Check: The recipient's mail server checks if the email passes SPF and DKIM authentication.
DMARC Policy Evaluation: Based on the configured DMARC policy (none, quarantine, or reject), the server determines what to do with the email.
Reports Sent: The recipient’s mail server sends DMARC reports back to the domain owner, providing insights into email activity and unauthorised email attempts.

Why Has DMARC Adoption Been Slow?

Despite its benefits, DMARC adoption has been sluggish. Here’s why:

Complexity of Implementation - Setting up DMARC requires proper configuration of SPF and DKIM records, which can be confusing for businesses without dedicated IT teams.
Risk of Email Deliverability Issues - If DMARC is misconfigured, legitimate emails could be rejected or marked as spam, disrupting communication. This risk makes many hesitant to enforce strict policies.
Lack of Awareness - Many businesses don’t realise that their domains can be exploited for email spoofing. Without awareness of the risks, there’s little urgency to adopt DMARC.
Perceived as a ‘Big Business’ Solution - Some SMEs believe DMARC is only necessary for large enterprises, not realising that any domain can be targeted by email fraud.
The "Set It and Forget It" Mindset - Some companies implement DMARC at the none policy level for reporting purposes but never move to stricter enforcement (quarantine or reject).

How to Set Up DMARC for Your Domain

To implement DMARC, you need access to your domain’s DNS settings. Here’s how to do it step by step.

Step 1: Set Up SPF (Sender Policy Framework)

SPF helps verify that emails sent from your domain come from authorised mail servers.

1. Log into your DNS provider (e.g., Ostratto Hosting, GoDaddy, 123Reg.
2. Locate the DNS settings for your domain.
3. Add a TXT record with the following format:

v=spf1 include:mailprovider.com -all

Replace mailprovider.com with your email service provider (e.g., Google Workspace, Microsoft 365).
The "-all" means that emails not listed in SPF should be rejected.

4. Save the record and allow time for propagation.

Step 2: Set Up DKIM (DomainKeys Identified Mail)

DKIM adds a cryptographic signature to emails, verifying their authenticity.

1. In your email provider’s admin panel, look for DKIM settings.

2. Enable DKIM and generate a public key.

3. Add a TXT record in your DNS settings using the provided values.

4. Save the record and enable DKIM signing.

Step 3: Configure DMARC

Once SPF and DKIM are in place, set up DMARC to define how unauthorised emails should be handled.

1. In your DNS settings, add a new TXT record for _dmarc.yourdomain.com.

2. Use the following format:

v=DMARC1; p=none; rua=mailto:dmarc-reports@yourdomain.com; ruf=mailto:dmarc-failures@yourdomain.com; pct=100;

p=none: This starts DMARC in monitoring mode (change to quarantine or reject later).
rua: Email address to receive aggregate reports.
ruf: Email address to receive forensic reports.
pct=100: Applies the policy to 100% of emails.

3. Save the record and wait for propagation.

Step 4: Monitor Reports & Adjust Policy

1. Use DMARC report analysis tools like DMARC Analyzer, Agari, or Postmark to interpret reports.

2. If all legitimate email sources pass DMARC, update the policy:

p=quarantine or p=reject

3. Continue monitoring to ensure no critical emails are affected.

Final Thoughts

DMARC is a crucial tool for preventing email spoofing and phishing attacks, yet its adoption remains slow due to its perceived complexity and risk of email deliverability issues. However, with careful setup and monitoring, businesses can implement DMARC effectively without disrupting legitimate email flow.

If you're still unsure about setting up DMARC for your domain, or would like this to be taken care of - we're just a message away.

Zoho AI Agents Are Coming

Mon, 17 Feb 2025 08:00:00 +0000

Zoho is no stranger to innovation, and their latest project—AI Agents—is set to redefine how businesses interact with their software. These smart assistants aren’t just about automating repetitive tasks; they’re designed to proactively enhance decision-making, optimize workflows, and improve customer interactions.

With AI rapidly changing the business landscape, staying ahead of the curve is crucial. Let’s explore what Zoho’s AI Agents could mean for your business.

What Are Zoho AI Agents?

AI Agents are Zoho’s next evolution in automation—virtual assistants that not only execute tasks but also learn, adapt, and make intelligent recommendations based on your business data. Think of them as an extension of your team, working seamlessly across Zoho’s suite of apps to boost efficiency and productivity.

They’re expected to leverage machine learning, natural language processing (NLP), and deep integration with Zoho’s ecosystem, enabling businesses to get more done with less effort.

How Will Zoho AI Agents Work?

Zoho’s AI Agents are designed to function as intelligent copilots, helping businesses by:

Automating Routine Tasks – AI Agents can handle data entry, follow-ups, and report generation, freeing up time for more strategic work.
Providing Data-Driven Insights – From sales forecasting to customer sentiment analysis, AI will surface insights that drive better decision-making.
Enhancing Customer Support – AI Agents in Zoho Desk and CRM will resolve queries, suggest responses, and even predict customer needs.
Personalising User Experiences – Whether in marketing, HR, or finance, AI Agents will tailor interactions based on user behavior and preferences.

Key Features to Expect

While details are still emerging, here’s what we anticipate from Zoho’s AI Agents:

1. Context-Aware Assistance

AI Agents will analyse your historical data and ongoing workflows to offer real-time, contextual recommendations. Whether you’re responding to a customer ticket or approving an invoice, the AI will suggest the next best action.

2. Conversational AI & Voice Commands

Interacting with AI will be more intuitive. Expect chatbot functionality, voice-based commands, and smart replies embedded into Zoho apps, making it easier to execute tasks without switching screens.

3. Predictive Analytics & Smart Decision-Making

Imagine getting notified before a customer churns or having your CRM suggest the best follow-up time for a lead—AI Agents will use predictive analytics to keep you ahead of the game.

4. Seamless Cross-App Integration

AI Agents won’t be confined to just one Zoho product. They will work across CRM, Desk, Books, People, and more, ensuring smooth automation and insights across all departments.

5. Security & Compliance Built-In

With AI handling sensitive data, security is a priority. Zoho’s AI Agents are expected to follow strict compliance protocols, ensuring data privacy and integrity.

Why This Matters for Your Business

The introduction of AI Agents marks a shift from reactive automation to proactive intelligence. Instead of manually setting rules and triggers, businesses will be able to rely on AI to anticipate needs and take action automatically.

For small and medium-sized businesses, this means:

Reduced workload for teams – More time to focus on strategy and growth.
Smarter customer interactions – AI-powered personalization leads to better engagement.
Faster decision-making – Real-time insights drive efficiency and profitability.
Enhanced operational efficiency – Workflows become smoother and more automated.

When Can We Expect Zoho AI Agents?

While Zoho hasn’t released an official launch date, early developments suggest that AI Agents will be rolled out gradually across their suite in late 2025. Beta programs and early access trials may be available sooner for select users.

If you’re already using Zoho, now is the perfect time to optimise your workflows so you’re ready to take full advantage of AI Agents when they arrive.

Final Thoughts

Zoho AI Agents represent the future of business automation—smarter, more intuitive, and deeply integrated with your day-to-day operations. As AI continues to evolve, businesses that embrace these innovations early will gain a competitive edge.

Want to stay ahead of the curve? Ostratto is here to help. We specialize in Zoho implementations, automation, and AI-driven business solutions. Contact us today to see how we can prepare your business for the future of AI-powered productivity.

Streamlining Natural Burial Ground Management: Leedam's Digital Transformation

Mon, 30 Dec 2024 17:21:35 +0000

Leedam Natural Burial, a leading provider of natural burial grounds across multiple sites in the UK, faced significant operational challenges managing their diverse locations through manual, spreadsheet-based systems. Their existing process relied heavily on fragmented data management across multiple registers, TypeForms, and daybooks, making it increasingly difficult to track burial plots, manage customer interactions, and maintain accurate inventory across their growing number of sites.

The business was managing critical sales and inventory data through a complex web of spreadsheets, with separate registers for each burial ground, creating risks in data accuracy and making it challenging to maintain a unified view of their operations. This fragmented approach was particularly problematic when handling multiple site requirements and was limiting their ability to scale efficiently.

Ostratto partnered with Leedam to implement a comprehensive Zoho CRM solution, transforming their burial ground management from a spreadsheet-dependent system to an integrated, automated platform. This digital transformation project focused on unifying their data management while maintaining the specific requirements for each unique burial ground location.

The Task

Ostratto was commissioned to implement a comprehensive CRM system that would consolidate Leedam's fragmented data management systems. The challenge was to transform multiple spreadsheet-based registers and forms into a streamlined, digital workflow that could handle multiple burial sites, varying location requirements, and complex inventory management. The system needed to manage everything from initial inquiries to plot allocation while maintaining accurate records across all locations.

Centrally Managed

The system required the capability to consolidate multiple site registers into a single, manageable platform while maintaining distinct tracking for each location. This meant creating a unified system that could handle different burial grounds' specific requirements while providing comprehensive oversight.

Process Automated

The solution had to streamline the entire customer journey from initial inquiry to plot allocation, with automated workflows replacing manual data entry. This required creating seamless connections between forms, CRM, and documentation processes.

Accurate

The platform needed to deliver precise tracking of available plots across all locations, preventing double-booking and maintaining accurate records of plot status. This meant implementing sophisticated inventory management that could handle the unique nature of burial ground plots.

Integration-Ready

The system needed to work seamlessly with existing tools while establishing a foundation for future digital enhancements, strengthening Leedam's technology investment and enabling future growth.

Products Featured

Leveraging our wide range of products and services, we implemented the correct tools to achieve the objective.

Zoho CRM

A customer relationship management solution that brings sales, inventory, and customer management together in one place.

View Product

Professional Services

Designing, implementing and maintaining the solution to meet requirements was all completed in-house by Ostratto.

View Service

Ostratto Support

Dedicated helpdesk support ensures users confidence in knowing they are technically supported at all times.

View Service

Implementation

The entire approach was then designed around these requirements, plus a few extras that would enhance the solution.

Centrally Managed

We transformed Leedam's ten separate site registers into a unified CRM system, creating a single source of truth for all burial ground data. The implementation included setting up custom modules to handle the specific requirements of each location while maintaining standardized data structures.

We developed custom views and filters that allow staff to quickly access site-specific information while maintaining the ability to generate cross-site reports and analytics. This centralization eliminated the need to maintain and update multiple spreadsheets, significantly reducing the risk of data inconsistencies.

Process Automated

The implementation replaced manual data entry with automated workflows throughout the customer journey. We migrated 12 different TypeForms to Zoho Forms, creating seamless integration with the CRM. Each form submission automatically creates or updates relevant records, triggering appropriate notifications and next steps.

The system generates required documentation automatically, from initial quotes to final certificates, pulling accurate data directly from the CRM. This automation extends to the sales process, with structured stages guiding staff through each step while maintaining compliance with burial ground regulations.

Accurate

We implemented a robust data management system that ensures precise tracking of every plot across all locations. The solution includes automated validation checks to prevent double-booking and maintains real-time inventory status.

We created custom fields and workflows to track the various stages of plot allocation, from available to reserved to occupied, with clear audit trails of all changes. The system automatically updates plot status based on sales progression, ensuring that staff always work with current, accurate information. This precision was extended to the creation of certificates and burial notices, eliminating manual data entry errors.

Integration-Ready

The solution was built on Zoho's platform, enabling immediate integration with complementary tools like Zoho Forms and Zoho Writer for document generation.

The system architecture was designed to accommodate growth, whether through adding new burial grounds or implementing additional features. This forward-thinking approach ensures the system can evolve alongside Leedam's business needs.

Result

The implementation of Zoho CRM has fundamentally transformed Leedam's natural burial ground operations, consolidating ten separate registers and twelve different forms into a single, powerful platform.

Manual data entry across multiple spreadsheets has been eliminated, reducing administrative time by 70%, while the automated form-to-CRM workflow has cut data entry errors by 95%. The new system has virtually eliminated plot allocation errors through automated inventory tracking, with all documentation now generated automatically from verified CRM data, ensuring consistency across all burial grounds.

Response times to inquiries have improved, with automated workflows ensuring consistent follow-up, while the streamlined process from initial contact to plot allocation has reduced the average transaction time. The platform has enabled Leedam to handle more inquiries without increasing administrative overhead, and the scalable system can easily accommodate new burial grounds without requiring additional administrative processes. Updates that previously required changes to ten different registers are now made instantly in one central location, with changes immediately reflected across all relevant documentation.

Digital form integration has made it easier for customers to submit information, while automated document generation has accelerated the delivery of certificates and burial notices. Most significantly, the improved efficiency has allowed staff to focus more time on customer care and site development.

The implementation has provided Leedam with a robust foundation for future growth, capable of handling increasing demand while maintaining the highest standards of accuracy and service.

At Ostratto, we're fundamentally customer-success focused. This means instead of designing solutions based on our expectations, we focus on customer requirements and needs to ensure their success. In turn, we find success in shared success as our customers' trusted technical consultancy partner whom they can rely upon.

We solve complex business problems with cutting-edge technology, whilst keeping everything simple for our customers. Be sure to check out other examples of how we have helped businesses make their work, less work.

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Case Study: Transforming Quote Generation for a Leading Solar Energy Provider

Tue, 03 Dec 2024 15:19:00 +0000

Solarsense, established as a leading solar energy provider in the South West of England, faced growing pains with their manual quoting system. With a team of field consultants handling complex solar installations nationwide, the company needed a solution that could match their reputation for excellence.

The business was relying on spreadsheet-based quotes that required office access, limiting their ability to serve customers efficiently. This created a significant bottleneck in their sales process, particularly affecting their energy consultants who needed to generate accurate quotes during site visits.

Solarsense partnered with Ostratto to implement a comprehensive Zoho CRM solution, transforming their quote generation from a desk-bound process to a mobile-friendly, automated system. This digital transformation project focused on enabling field consultants to create professional quotes on-site while ensuring accuracy through automated calculations and product compatibility checks.

The Task

The primary challenge was to transform a complex, manual quoting process that required office access into a mobile-friendly system their field consultants could use anywhere. The solution needed to handle intricate product configurations, including solar panels, inverters, and mounting systems, while automatically calculating compatibility and pricing.

Beyond just digitising the process, the system needed to enable on-site quote generation, standardize proposal documents, and integrate e-signatures for faster deal closure. This required a careful balance between maintaining the detailed technical specifications necessary for solar installations while creating an intuitive interface that consultants could use efficiently during customer visits.

Mobile-First

The system required seamless functionality across all mobile devices, enabling consultants to generate professional quotes during customer site visits. This mobile-first approach meant designing an interface that balanced complex technical capabilities with intuitive usability, ensuring consultants could work efficiently from any location.

Automated & Intelligent

The platform needed to deliver smart automation throughout the quote generation process, from initial product selection to final proposal creation. This meant implementing sophisticated rules for product compatibility and automated pricing calculations, while maintaining accuracy and eliminating manual checks.

Instantly Updatable

A central requirement was the ability to push real-time updates across the entire system, ensuring all users had immediate access to the latest product specifications and pricing information. This real-time synchronization needed to work across all devices, eliminating the risk of outdated information in quotes.

Integration-Ready

The solution required seamless integration between multiple systems, connecting CRM functionality, quote generation, and e-signature capabilities into a single, cohesive workflow. This integrated approach needed to support future scalability while maintaining consistent performance across platforms.

Products Featured

Leveraging our wide range of products and services, we implemented the correct tools to achieve the objective.

Zoho CRM

A customer relationship management solution that brought together sales and customer management in one place.

View Product

Professional Services

Designing, implementing and maintaining the solution to meet requirements was all completed in-house by Ostratto.

View Service

Ostratto Support

Dedicated helpdesk support ensures users confidence in knowing they are technically supported at all times.

View Service

Implementation

The entire approach was then designed around these requirements, plus a few extras that would enhance the solution.

Mobile-First

We transformed Solarsense's field operations by optimizing Zoho CRM's mobile interface specifically for their consultants. The solution focused on streamlined mobile layouts that displayed essential quote information at a glance, while enabling one-touch quote generation during site visits.

Understanding the challenges of rural installations, we implemented offline access capabilities, ensuring consultants could continue working even in areas with poor connectivity. The mobile interface was extensively tested and refined based on consultant feedback to ensure optimal usability on both tablets and phones.

Automated & Intelligent

The heart of the solution lay in creating a sophisticated CPQ system with custom rules for solar panel compatibility. We developed automated calculations that instantly determined system sizing and pricing based on site requirements.

The system was programmed to make smart product suggestions based on installation parameters, while automated validation checks ensured technical specifications were always accurate. This eliminated the manual cross-checking that previously consumed hours of consultant time.

Instantly Updatable

We established a centralized product catalog that served as a single source of truth for all product information. Real-time updates to pricing and specifications were immediately reflected across the entire system, with automated synchronization ensuring consistency.

Push notifications kept all users informed of product changes, while version control for proposal documents eliminated confusion over outdated templates. The quick-update tools we developed allowed product information to be modified efficiently when needed.

Integration-Ready

The implementation connected Zoho CRM, CPQ, and Sign into a seamless workflow that eliminated manual handoffs between systems. We integrated automated document generation through Zoho Writer, creating standardized proposals that maintained brand consistency.

The e-signature process was streamlined for quick customer approval, while automated follow-up workflows kept deals moving forward. All integrations were built on a scalable framework, allowing for easy addition of new features as Solarsense continues to grow.

" Ostratto helped us implement Zoho without any of the usual tech headaches. No jargon, no complications - just practical solutions that work. Their training was spot-on, and whenever we need help, they're quick with clear answers. Our teams now spend less time on admin and more time on actual work."

James Molloy

Head of Quality & Support

Result

The implementation of Zoho CRM transformed Solarsense's sales operations, delivering immediate and measurable improvements across the business.

Quote generation time plummeted by 75%, with field consultants now creating and sending professional quotes during initial site visits rather than returning to the office. The automated system virtually eliminated pricing errors and incompatible product combinations, while reducing quote revision requests.

Consultants now report 100% reliability in generating quotes on-site, regardless of location, with the mobile-first approach enabling a 40% increase in daily site visits. The streamlined process has allowed Solarsense to handle 60% more quotes a week without increasing administrative overhead, while e-signature integration has reduced closing time from days to hours, with an increase in proposals signed within 24 hours of presentation.

Perhaps most significantly, the improved efficiency has allowed consultants to focus more time on customer relationships, resulting in an increase in conversion rates. Product updates that previously took days to implement are now instant, ensuring all team members work with current, accurate information at all times.

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Streamlining HR Operations: The Thinking Traveller's Digital Transformation

Wed, 02 Oct 2024 09:46:00 +0000

The Thinking Traveller, a luxury villa rental company operating across multiple countries, faced significant operational challenges as their team expanded to 150 employees across three countries. Their existing manual HR processes, which included paper-based onboarding, spreadsheet-driven leave management, and decentralized employee records, were becoming increasingly complex and time-consuming. With different regional requirements for each location and a growing need for standardized processes, the company needed a solution that could scale with their ambitious growth plans while maintaining compliance across all territories.

The business was managing critical HR functions through a combination of emails, spreadsheets, and physical documents, creating bottlenecks in employee onboarding and leave management. This fragmented approach was particularly challenging when handling multiple regions' specific requirements and was limiting their ability to maintain consistent HR practices across their expanding operation.

The Thinking Traveller partnered with Ostratto to implement a comprehensive Zoho People solution, transforming their HR management from a manual, location-dependent process to an automated, globally accessible system. This digital transformation project focused on standardizing processes while maintaining the flexibility needed for regional variations in HR requirements.

The Task

Ostratto was commissioned to implement a comprehensive HR management system using Zoho People. The challenge was to transform manual HR processes into a streamlined, digital workflow that could handle multiple locations, varying regional requirements, and complex onboarding procedures. The system needed to manage everything from employee documentation to leave requests while maintaining compliance across different territories.

Globally Adaptable

The system required the flexibility to handle multiple territories with different HR requirements, forms, and processes. This meant creating location-specific workflows while maintaining consistent company-wide standards across three different countries.

User-Friendly

The solution had to be accessible and easy to use for both HR administrators and employees, with self-service capabilities for common HR tasks. This required intuitive interfaces and clear guidance for users across all levels of technical ability.

Process-Driven

The platform needed to enforce structured HR workflows with automated approval processes, from employee onboarding to leave management. This meant implementing clear procedures that could be consistently followed across all departments and locations.

Integration-Ready

The system needed to work seamlessly within the existing Zoho ecosystem while remaining flexible enough to accommodate future growth and additional integrations, strengthening The Thinking Traveller's technology investment.

Products Featured

Leveraging our wide range of products and services, we implemented the correct tools to achieve the objective.

Zoho People

A comprehensive HR management platform that streamlines employee data management, onboarding, and HR processes.

View Product

Professional Services

Designing, implementing and maintaining the solution to meet requirements was all completed in-house by Ostratto.

View Service

Ostratto Support

Dedicated helpdesk support ensures users confidence in knowing they are technically supported at all times.

View Service

Implementation

The entire approach was then designed around these requirements, plus a few extras that would enhance the solution.

Globally Adaptable

We configured Zoho People to handle multiple territories by creating location-specific forms and workflows for each country. This included setting up 17 departments, 70 designations, and specific processes for three different locations, ensuring compliance with local requirements while maintaining global consistency. Each location received its own customized set of HR documents and processes, with automated translations where needed.

The system was structured to automatically route employees through the correct regional processes based on their location, while still maintaining centralized oversight for global HR managers. This careful balance of local autonomy and central control ensured that regional HR requirements were met without creating administrative silos.

User-Friendly

The platform was set up with intuitive self-service features, including an automated leave management system with eight different leave types and clear approval workflows. We created standardized processes for common HR tasks, making it easy for both administrators and employees to navigate the system.

The interface was customized with role-based dashboards, ensuring users only see the information and options relevant to their position. Mobile accessibility was prioritized throughout the implementation, allowing employees to submit requests and access information from any device. Training materials and help documentation were created specifically for each user type, from basic employees to HR administrators.

Process-Driven

We implemented structured workflows for employee onboarding, including automated document collection, digital signatures for contracts, and customized forms for each location. The system was configured with up to 10 forms per location, covering everything from basic employee information to specific regional requirements. Each form was designed with smart validation rules to ensure data accuracy and completeness.

The onboarding workflow was built with conditional logic that adapts based on the employee's role, department, and location, automatically triggering relevant tasks and notifications. This eliminated the need for HR to manually track and assign onboarding tasks, reducing the risk of missed steps in the process.

Integration-Ready

The solution was implemented as part of the Zoho One ecosystem, ensuring seamless integration with existing tools while establishing a foundation for future expansion. This included setting up automated workflows that could be easily modified as the business continues to grow.

The architecture was designed with scalability in mind, allowing for easy addition of new locations, departments, or HR processes without requiring significant system changes. This forward-thinking approach ensures the system can evolve alongside The Thinking Traveller's business needs.

Result

The implementation of Zoho People transformed The Thinking Traveller's HR operations, delivering significant improvements across their global business.

Manual onboarding processes that previously took days are now completed in hours through automated workflows. The system successfully manages 150 employees across three countries, with standardized processes reducing administrative time by up to 60%.

Leave management, previously a complex manual process, is now handled automatically with location-specific rules and approval workflows. HR documentation is now 100% digitised, with all forms and processes accessible through a single platform. The self-service capabilities have reduced HR inquiry response times, while the automated onboarding process has cut new employee setup time significantly.

Most importantly, the system has provided a scalable foundation for future growth, capable of handling increasing employee numbers without additional administrative overhead.

Chat with us today