For as long as Kenya has worn the "Silicon Savannah" label, a familiar complaint has trailed it. The tech opportunity, the argument goes, lives almost entirely in Nairobi. Coders in Kilifi, entrepreneurs in Embu, and trainers in Taita Taveta have often had to watch the digital economy grow from a distance, mostly through their phone screens. Microsoft and the Stanbic Kenya Foundation are betting they can change that pattern, at least for artificial intelligence skills. The two organisations, working alongside Konza Technopolis and Pathways Technologies, have expanded the Microsoft Elevate AI National Skilling Initiative into five counties outside the capital. It is a small but telling experiment in whether AI training in Kenya can be built around the country rather than just around its biggest city.<h2>What the Program Actually Does</h2>The initiative has so far trained 152 participants across Kwale, Kilifi, Mombasa, Taita Taveta, and Embu. These are coastal and eastern counties that rarely feature in conversations about Kenya's tech sector, despite hosting large populations of youth, small traders, and informal businesses that could genuinely use AI tools.<ad-spot></ad-spot> Rather than run generic coding bootcamps, the program leans on Stanbic Kenya Foundation's existing relationships with TVETs (Technical and Vocational Education and Training institutions) and community networks. Mercy Githanji, who heads the Stanbic Foundation, has described digital literacy as one of the foundation's core pillars, with the current push aimed at building the capacity of instructors who can then pass AI skills on to students and entrepreneurs long after the initial training ends. That train-the-trainer approach matters more than it might seem. A one-off workshop teaches a few dozen people. A trained instructor at a vocational college keeps teaching for years. Microsoft's Winnie Karanu, the company's AI Skills Director, has pointed to county-level engagements and community-based platforms as the mechanism for reaching people outside Kenya's major cities. In practice, this means the training is designed to plug into what local economies already run on: agriculture, logistics, and small business administration, rather than abstract programming concepts that may have little immediate use for a trader in Kwale or a farmer in Embu.<h2>Why This Fits the Digital Masterplan</h2>This expansion does not exist in isolation. It sits inside Kenya's broader Digital Masterplan (2022-2032), which set out four pillars for the country's digital transformation: infrastructure, government services, digital skills, and innovation and enterprise. The skills pillar alone targets training 20 million citizens, including 300,000 public servants, over the plan's ten-year run. What is notable here is the geographic intent baked into the plan from the start. The Masterplan calls for widespread rural and county-level ICT deployment, including a network of digital hubs meant to bring training and government services closer to citizens who are not in Nairobi. Konza Technopolis, itself a flagship project of that plan, is meant to serve as an anchor for exactly this kind of decentralised skills delivery, and its involvement in the Microsoft-Stanbic program is a fairly direct expression of that mandate.<ad-spot></ad-spot> Seen this way, the five-county rollout is not just a corporate social responsibility gesture. It is one of the more concrete, on-the-ground attempts to make good on a policy commitment that Kenya made years ago and has struggled, like most ambitious ten-year plans, to fully execute.<h2>The Bigger Picture: Microsoft's Kenya Bet</h2>This program is also one thread in a much larger investment. Microsoft has previously committed to providing AI and cybersecurity education to a million Kenyans by 2027, alongside building what it describes as Africa's first dedicated AI skilling centre at Konza Technopolis. The company has also worked with the Kenyan government, UNDP, and the Public Service Commission on a Centre of Competence aimed at training public servants, and it has partnered with Konza on a separate AI skills programme focused on women's leadership in tech. Taken together, these initiatives paint a picture of Microsoft treating Kenya less as a single market to sell software into and more as a talent pipeline to build. That is not purely altruistic. A company that helps train the next generation of AI-literate workers in East Africa also positions itself to recruit from that pool and to embed its own tools as the default choice in classrooms and workplaces. It is worth naming that dynamic even while acknowledging the genuine value the training offers to participants who would otherwise have limited access to it.<h2>Does Decentralized Training Actually Work?</h2>The honest answer is that 152 trained participants across five counties is still a modest number against Kenya's population and the scale of the country's youth unemployment challenge. The real test will be whether this becomes a sustained, expanding program or a pilot that fades once the initial funding cycle and press coverage move on. There is reason for cautious optimism, though. The train-the-trainer model is the right structural choice for reaching beyond Nairobi, since it does not depend on flying instructors in and out. Building around existing TVET networks also means the program is riding on infrastructure that already exists rather than trying to create parallel institutions from scratch. And tying the curriculum to agriculture, logistics, and small business tasks means the skills are more likely to be used immediately rather than shelved as abstract knowledge. The bigger question is whether other counties, especially those in Kenya's north and northeast that face even steeper connectivity and infrastructure gaps, will see similar investment. Coastal and eastern counties benefit from relatively better road networks, internet penetration, and proximity to Mombasa's commercial activity. A genuine test of "devolving AI" will come when programs like this one reach counties where the barriers are not just about training access but about basic connectivity.<h2>What This Means for Kenyan Businesses and Job Seekers</h2>If you run a small business or work in training and vocational education outside Nairobi, this initiative is worth watching closely, and possibly applying to. The practical AI skills being taught, things like using AI for inventory forecasting or automating basic customer service, are exactly the kind of low-cost efficiency gains that can help a small enterprise compete without needing a large tech budget.<ad-spot></ad-spot> For job seekers and instructors in the five counties involved, the program also offers something harder to quantify: proximity to a growing part of the economy that has historically required relocating to Nairobi to access. Whether that proximity translates into real employment outcomes over the next few years will be the clearest indicator of whether Kenya's AI skilling push is genuinely reaching beyond the capital, or simply talking about it.

Devolving AI: Inside Microsoft and Stanbic's Push to Move Tech Skills Beyond Nairobi

It was one of the most ambitious tech deals ever announced on African soil. In May 2024, President William Ruto stood before cameras during a state visit to Washington, D.C., and announced that Microsoft and UAE-based artificial intelligence firm G42 would invest $1 billion to build a geothermal-powered data center in Olkaria, Kenya. The plan was bold, the setting was dramatic, and the symbolism was hard to miss. Kenya would become a digital hub for East Africa, powered entirely by clean, renewable geothermal energy from the Great Rift Valley.Two years later, that dream has officially been suspended.President Ruto himself confirmed the news in late April 2026, speaking to grassroots leaders in Nairobi. His explanation was blunt: the data center would have required roughly one-third of Kenya's total installed electricity capacity, and the national grid simply cannot support it. "To switch on that one data center, we would need to shut off power for half the country," Ruto reportedly said. "That's when I knew there was a problem."This is a story about infrastructure ambition meeting hard infrastructure reality. And it raises questions that go well beyond Kenya's borders.<h2>What Was the Deal, and What Was Promised?</h2><img src="https://cdn.calebms.com/articles/3586fec8-b1eb-4f62-8bd6-fdebe6be337a.jpg" alt="70755.jpg" data-caption="Olakiria II Geothermal Power Station. ">The Microsoft-G42 partnership was announced amid significant fanfare. G42, led by CEO Peng Xiao, was to lead the initial investment and handle construction on the Olkaria geothermal field in Naivasha, roughly 100 kilometres northwest of Nairobi. The site was chosen deliberately: Olkaria is home to Kenya's state-owned Kenya Electricity Generating Company (KenGen), which operates four geothermal power plants in the region with an installed geothermal capacity of approximately 800 megawatts.<ad-spot></ad-spot>The data center would run Microsoft Azure for a new East Africa Cloud Region, giving businesses and governments across the region access to cloud computing services. The first phase was to have a capacity of 100 megawatts and was expected to be operational within 24 months of the deal being signed, putting the target date squarely at May 2026. Ultimately, the project was designed to scale up to a full 1 gigawatt of power.On paper, it looked like the ideal convergence of technology and sustainability. Kenya has one of the cleanest energy mixes on the African continent, with renewables accounting for about 80% of the national energy mix. Geothermal energy, unlike solar or wind, is baseload power: it runs 24 hours a day, 7 days a week, making it ideal for the constant, uninterrupted power demands of a large data center. Kenya even ranks seventh in the world for installed geothermal capacity.The deal was also framed as a geopolitical win. It was orchestrated partly by the Biden administration as a way to strengthen US-Kenya ties and counter growing Chinese influence in East Africa.<h2>Why It Stalled: The Numbers Don't Lie</h2>The problem, as it turns out, was always hiding in plain sight.Kenya's total installed electricity capacity is approximately 3,000 megawatts. The Microsoft-G42 data center, at full buildout, would have consumed 1,000 megawatts, which is one-third of the entire national grid. Even the first phase alone, at 100 megawatts, represents a significant chunk of what the country can reliably generate and distribute.<ad-spot></ad-spot>But the crisis runs deeper than just the data center. Kenya is already struggling badly with its power situation. By the end of January 2026, the country's system peak demand stood at 2,439 megawatts against a firm capacity of only 2,495 megawatts, leaving a reserve margin of just 2.3%. On paper, Kenya appears to have nearly 800 megawatts of installed capacity to spare, but in practice, only about 56 megawatts of firm, reliable headroom remains. That is almost nothing.The grid's troubles don't stop there. In 2025, system losses due to unbilled or stolen electricity reached 23.36%, far above the regulator's allowable benchmark of 17.5%. Consumers in 2025 experienced an average of 8.39 hours of power cuts per month, nearly six times higher than the regulator's target of 1.5 hours. President Ruto himself admitted in November 2025, while speaking to Kenyans abroad in Doha, that the government was already carrying out deliberate load shedding between 5 pm and 10 pm in some areas just to keep the grid stable.No new interconnected power plants had been commissioned in the four years preceding 2025. A government moratorium on new power purchase agreements, imposed in 2021, was only lifted in December 2025 by the National Assembly. That moratorium created a gap in Kenya's capacity pipeline just as demand was accelerating, driven by industrial growth, electric vehicles, new data centers, and an aggressive domestic connectivity programme.Adding a 1 GW data center to this already strained system would not have been an upgrade. It would have been a catastrophe.<h2>The Political Anatomy of a Stalled Deal</h2>Beyond the technical realities, the timeline of this project's collapse reveals a pattern worth examining.Semafor had reported as far back as September 2025 that the project had stalled, with developers having never broken ground. Government officials, speaking anonymously, confirmed that Kenya's technology ministry had developed a concept note for the project and submitted it to the National Treasury to unlock funding. The National Treasury declined to approve it. By August 2025, both Kenyan officials and Microsoft executives already knew the May 2026 operational target would not be met.<ad-spot></ad-spot>G42 declined to comment when news of the suspension broke. Microsoft did not immediately respond to media requests.The announcement was made at a high-profile bilateral summit during Ruto's state visit to Washington. It checked every box for a presidential photo opportunity: a billion-dollar investment, a clean energy angle, a tech giant partner, and a development narrative for Africa. What it lacked was a feasibility study that took Kenya's existing grid realities seriously before the ink was signed.This is not the first time an ambitious deal has been announced at an international forum, only to quietly unravel when the details are stress-tested. Letters of Intent and Memoranda of Understanding do not build infrastructure. They announce intentions. The hard work, the grid assessments, the treasury approvals, the procurement timelines, those need to be done before the cameras show up.<h2>Kenya's Power Problem Is Not New. The AI Boom Makes It Urgent.</h2>Here is what makes this story particularly important to understand in 2026: the global demand for data center power is growing at a pace that was almost unimaginable five years ago.According to the <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.iea.org/reports/energy-and-ai/energy-supply-for-ai">International Energy Agency (IEA)</a>, data center electricity consumption surged by 17% in 2025 alone, with AI-focused data centers climbing even faster. Global data center electricity use is projected to roughly double from 485 terawatt-hours in 2025 to 950 terawatt-hours by 2030. That would represent about 3% of the entire world's electricity demand. The five largest tech companies combined spent more than $400 billion in capital expenditure in 2025 on infrastructure, and that figure is set to rise by a further 75% in 2026.Even developed nations with robust grids are struggling to cope. In the United States, data center demand could reach 74 gigawatts by 2028, with a projected shortfall of about 49 gigawatts in available power access, <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.morganstanley.com/insights/articles/powering-ai-energy-market-outlook-2026">according to Morgan Stanley Research. </a>US data centers used around 4% of the nation's electricity in 2023, and that share is expected to rise to between 7% and 12% by 2028. In Ireland, which has become a European tech hub, data centers already consume about 21% of the country's electricity, with the IEA projecting that share could rise to 32% by 2026.To address this, tech giants in the West are turning to nuclear energy. Microsoft struck a deal to reopen the Three Mile Island nuclear plant in the United States. The pipeline of agreements between data center operators and Small Modular Reactor (SMR) projects grew from 25 gigawatts at the end of 2024 to 45 gigawatts today. Goldman Sachs estimates that 85 to 90 gigawatts of new nuclear capacity would be needed to meet all projected data center power demand growth by 2030.These are the countries that Kenya was implicitly competing with for hyperscaler investment. And they are struggling with power supply despite having vastly more grid capacity, infrastructure redundancy, and capital to deploy new generation.Kenya has a 3 GW grid. The United States has a 1,200 GW grid.<h2>Kenya's Data Center Future: Smaller, Smarter, Staged</h2>None of this means Kenya cannot participate in the global data center economy. It means the participation must be calibrated to what the country can actually support right now.The good news is that Kenya's data center market is still growing. According to reports, Kenya accounts for more than three-quarters of fresh data center capacity expected in East African markets by 2030. The country's renewable energy mix, its relatively strong digital infrastructure, its position as East Africa's financial and technology hub, and the emergence of a local talent ecosystem all make it an attractive market.<ad-spot></ad-spot>More realistic projects are already moving forward. Nxtra, a subsidiary of Airtel Africa, began construction of East Africa's largest data center in Kenya's Tatu City in late 2025. The facility will be 44 megawatts in capacity, slated for completion this year, and is designed to support AI-driven solutions and cloud services for businesses, startups, and governments. That is a meaningful, appropriately scaled facility that does not require a third of the national grid to operate.Ruto has stated his intention to raise Kenya's power capacity to 10,000 megawatts by 2030, which he has linked to a controversial plan to raise $38 billion through asset sales and private capital. That target is ambitious to say the least, but it points in the right direction. Kenya needs to prioritise grid expansion before it can realistically court hyperscale data center investment.The question is not whether Kenya can host large data centers. It is whether Kenya can build the power base to support them. The answer, right now, is no. But with the moratorium on new power purchase agreements lifted, and with serious reform of transmission infrastructure underway, the conditions for a more viable future are slowly taking shape.<h2>What This Means for Kenya's Tech Ambitions</h2>There is a temptation to frame the suspension of the Microsoft-G42 deal as a failure or an embarrassment. That would be unfair. Ruto made the right call. Connecting a 1 GW data center to a 3 GW grid with barely 56 megawatts of firm headroom, in a country already experiencing daily load shedding, would have been genuinely reckless. Ordinary Kenyans, small businesses, hospitals, schools, and factories would have paid the price in the form of even worse, more frequent blackouts.What this story really highlights is the gap between the aspirational language of global tech summits and the grinding, unsexy work of building energy infrastructure. Kenya has world-class geothermal resources. It has a young, tech-savvy population. It has a growing startup ecosystem. But it cannot shortcut the need for reliable, sufficient electricity. The AI revolution is intensely power-hungry, and countries that want to host it need to have their energy house in order first.<ad-spot></ad-spot>The lesson for Kenya's policymakers is not to stop dreaming big. It is to do the feasibility work before the cameras arrive. The lesson for tech investors is that Africa's digital potential is real, but so are its infrastructure constraints, and those constraints demand honest engagement, not just headline-grabbing MOUs.Kenya will get its moment. But it will need to build the grid first.

Kenya Suspends the $1 Billion Microsoft-G42 Data Center: A Bold Deal That the Grid Could Not Handle

For the past two years, AI agents browsing the web have been doing something deeply inefficient. When an AI assistant tries to book a flight, fill a form, or add a product to a cart on your behalf, it does not understand your website the way a human does. It looks at it like a photograph — analysing pixels, guessing which button to click, scraping raw HTML, and burning through hundreds or thousands of tokens just to figure out where the search bar is.If the button moved five pixels between deployments, the agent breaks. If you changed your CSS class names, the agent breaks. If your checkout flow has a dynamic step, the agent breaks.This is the messy, expensive, unreliable reality of how AI has been interacting with the web until now. Google wants to change that — and what they shipped earlier this month has implications that reach well beyond Silicon Valley, including for developers and businesses building on the web in Kenya.<h2>The Old Way: AI as a Confused Tourist</h2>To understand why WebMCP matters, you need a clear picture of the problem it is solving.When an AI agent visits a website today, it has essentially three tools available. It can scrape the raw HTML and try to parse meaning from the structure. It can take a screenshot and send it to a multimodal vision model to interpret visually. Or it can try to manipulate the DOM directly — finding elements by their IDs, classes, or positions and clicking them programmatically.All three approaches share the same fundamental weakness: the agent is guessing. It is inferring intent from presentation. A button labelled "Continue" could mean "proceed to payment" or "dismiss this popup" — the agent has to figure that out from context, and it frequently gets it wrong.<ad-spot></ad-spot>The result is agents that are slow, expensive to run, and brittle. A single UI change on your website can break an automation that was working perfectly the day before. And for every task completed successfully, there are dozens of token-burning attempts that failed silently or produced the wrong outcome.This is the problem that has limited browser-based AI agents from becoming genuinely useful at scale. Until now, the gap between what AI agents could theoretically do on the web and what they could reliably do in practice has been enormous.<h2>What WebMCP Is</h2>On February 10, 2026, the Google Chrome team launched WebMCP — the Web Model Context Protocol — as an early preview in Chrome 146 Canary. It was developed jointly by engineers at Google and Microsoft and is being incubated through the W3C's Web Machine Learning community group, which means this is not a Google-only experiment. It is the beginning of a proposed web standard with cross-industry backing.The core idea is straightforward: instead of making AI agents guess how your website works, WebMCP lets your website tell them directly.It works through a new browser API called `navigator.modelContext`. Using this API, your website publishes what Google calls a "Tool Contract" — a structured list of things the agent is allowed to do and exactly how to do them. Instead of an agent trying to visually locate a booking form and click through it field by field, your website simply exposes a function like `bookFlight(destination, date, passengers)`. The agent calls that function directly. No screenshot analysis. No DOM guessing. No pixel counting.<ad-spot></ad-spot>Google's André Cipriani Bandarra, who led the announcement, put it this way: by defining these tools, you tell agents how and where to interact with your site — whether it is booking a flight, filing a support ticket, or navigating complex data. The direct communication channel eliminates ambiguity and allows for faster, more robust agent workflows.The early numbers reflect that. Benchmarks from the preview show approximately a 67% reduction in computational overhead compared to traditional visual agent-browser interactions, with task accuracy sitting around 98%. Both figures need broader real-world validation, but the directional improvement is significant.<h2>The Two APIs: Declarative and Imperative</h2>WebMCP gives developers two ways to make their sites agent-ready, depending on how complex their workflows are.The Declarative API is the simpler option. It works by adding new attributes directly to standard HTML forms. If your website already has a well-structured form — a contact form, a search bar, a booking widget — you can expose it to agents with minimal additional code. This is the entry point for most websites, and it requires no new backend infrastructure.The Imperative API is for more complex, dynamic interactions. It uses JavaScript's `navigator.modelContext.registerTool()` method to define richer tool schemas that can handle multi-step workflows, conditional logic, and dynamic state. If you are building something like a multi-step checkout, a product configurator, or a support ticket system with branching logic, this is the API you would use.Both APIs are built with security and user consent in mind. The browser acts as a secure proxy between the agent and your site, and sensitive actions require explicit user confirmation before execution. There is also a `clearContext()` method to wipe shared session data, preventing agents from retaining information across sessions without consent.The specification is explicit that WebMCP is designed for cooperative, human-in-the-loop workflows — not silent, unsupervised automation. The user is present. The agent acts on their behalf with their knowledge.<h2>This Is Not Anthropic's MCP — But They Work Together</h2>If you have been following AI infrastructure news, you will notice the name overlap. Anthropic's Model Context Protocol — MCP — has been gaining significant adoption among developers building server-side AI integrations. The names are similar and the goals are related, but they solve different problems.Anthropic's MCP operates on the server side. It connects AI platforms to back-end services through API integrations — no browser required. It is designed for automation that happens without a human watching, such as an AI agent querying a database, calling an external API, or managing files on a server.WebMCP operates on the client side, inside the browser tab. It is designed for situations where the user is present and the interaction benefits from the shared visual context of an active browser session. Think of it this way: Anthropic's MCP is for when no human is watching. WebMCP is for when the user is right there, ready to step in if something goes wrong.The two standards do not compete — they complement each other. A travel company, for example, might run an Anthropic MCP server for direct API integrations with ChatGPT and Claude, while simultaneously implementing WebMCP on their consumer-facing booking page so that browser-based agents can interact with the checkout flow in the context of the user's live session.<ad-spot></ad-spot><h2>The Cloudflare Connection: Reading and Acting</h2>We covered <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.techinkenya.com/articles/cloudflare-introduces-markdown-for-ai-agents-a-quiet-revolution-with-major">Cloudflare's Markdown endpoint for AI agents </a>in a previous piece — a feature that lets AI systems read your website's content cleanly, without parsing HTML noise, by exposing a structured text version of any page.WebMCP completes the other half of that picture.Cloudflare's Markdown endpoint solves the read problem: how do AI agents consume your content accurately and efficiently? WebMCP solves the action problem: how do AI agents do things on your website accurately and efficiently?Together, these two developments represent the infrastructure layer of what is increasingly being called the agentic web — a version of the internet designed not just for human visitors, but for AI agents acting on their behalf. The read layer and the action layer, shipped within weeks of each other, by two of the most widely used web infrastructure companies in the world.This is not a coincidence. It is a signal.<h2>What This Means for Kenyan Developers and Businesses</h2>Here is where the story gets practically important for anyone building on the web in Kenya.The shift to agentic web interactions is going to create a new axis of competitive advantage — and the gap between websites that are agent-ready and those that are not will become as significant as the gap between websites that had mobile-responsive design and those that did not. That transition took several years to play out. This one will move faster.For developers, WebMCP is worth exploring now, not later. The early preview program gives you access to documentation and demos before the broader rollout. Joining now means you understand the standard before your clients start asking about it. Given that WebMCP reuses existing front-end JavaScript rather than requiring new backend infrastructure, the implementation cost for a well-structured site is lower than it might appear. You are not rebuilding your site — you are adding a structured description of what it already does.For Kenyan startups and businesses with transactional websites — e-commerce, booking platforms, fintech products, SaaS tools — the case for paying attention is direct. As AI assistants become more capable and more widely used, users will increasingly ask their agents to complete tasks on their behalf rather than navigating websites manually. A Kenyan e-commerce platform that has implemented WebMCP will be one that AI assistants can use reliably on behalf of their users. One that has not will be one that agents fail on, abandon, or route around.The use cases Google has highlighted at launch — booking, e-commerce, and customer support — are precisely the categories where Kenyan digital businesses are growing fastest.For everyone else, the honest answer is that WebMCP is still an early preview and formal browser support across all major browsers is expected sometime in mid-to-late 2026, with Google I/O flagged as a probable venue for a broader announcement. You do not need to implement anything today. But you do need to understand what is coming and factor it into how you think about your web presence over the next 12 to 18 months.<ad-spot></ad-spot><h2>How to Access the Preview</h2>If you are a developer who wants to start testing now, here is how to get access:WebMCP is currently available in Chrome 146 Canary behind the "WebMCP for testing" flag at chrome://flags. To access the full documentation and demos, you need to join Google's Early Preview Program (EPP) via the Chrome for Developers blog at <a target="_blank" rel="noopener noreferrer nofollow" href="https://developer.chrome.com/blog/webmcp-epp">developer.chrome.com/blog/webmcp-epp</a>.The EPP gives you early access to Chrome 146 features, direct feedback channels with the team, and the ability to test how different large language models interpret your tool descriptions before the standard goes public. Given that vague tool descriptions can cause models to produce incorrect outputs, the testing period is genuinely valuable — not just a formality.<h2>The Bigger Picture</h2>The USB-C analogy that Chrome's Khushal Sagar has used to describe WebMCP is worth sitting with. USB-C did not just make one type of device faster — it created a single, standardised interface that any device could use, replacing a fragmented landscape of proprietary connectors. WebMCP is attempting the same thing for AI agent interactions: one standard interface that any agent can use to interact with any website, replacing the current tangle of bespoke scraping strategies and fragile automation scripts.Whether WebMCP achieves that depends on adoption — by browser vendors beyond Chrome and by web developers who choose to implement it. With Google and Microsoft jointly shipping the code and the W3C providing institutional backing, the foundation is solid. The next six months will tell us whether the broader ecosystem follows.What is already clear is that the direction of travel is set. The web is becoming agentic. The infrastructure to support that — from Cloudflare's read layer to Google's action layer — is being built right now. The question for Kenyan developers and businesses is not whether this shift will happen. It is whether you will be ready when it does.

Devolving AI: Inside Microsoft and Stanbic's Push to Move Tech Skills Beyond Nairobi

Kenya Suspends the $1 Billion Microsoft-G42 Data Center: A Bold Deal That the Grid Could Not Handle

Google Just Changed How AI Interacts With Websites. Here Is What Every Kenyan Developer and Business Owner Needs to Know.