The company announced the changes on Monday, making AI Plus the lowest-priced paid AI subscription offered by a provider in the US market.

Vikas Kansal, product lead for Gemini AI subscriptions, said on X that the storage upgrade would reach users over the next few days.

Google AI Plus was introduced in January as an entry-level paid plan aimed at individual users and students. The service includes access to Gemini with higher usage limits, Omni Flash video generation, Google Flow creative tools, NotebookLM and AI-powered features in Gmail.

In Nigeria, alongside AI Plus at N7,700, Google still offers higher-priced plans. Google AI Pro costs N28,500 per month and includes 5TB of storage, expanded Gemini access and the company’s Pro model.

Google AI Ultra starts at N89,000 per month, offers at least 20TB of storage and provides significantly higher usage limits, as well as early access to new features.

The current price reduction follows a series of changes to Google’s AI subscription business this year. In April, the company increased storage on its AI Pro plan to 5TB without raising prices. A month later, it launched a new AI Ultra package and reduced the cost of its top-tier subscription from $250 to $200 per month.

With competition increasing among AI providers over subscription pricing, and premium plans taking over the market, companies have now started introducing cheaper options to attract more users.

This first became visible in India, one of the world’s fastest-growing AI markets. OpenAI launched ChatGPT Go there in August 2025 at about $4.60 per month, well below the price of its standard ChatGPT Plus subscription. Google followed with its own sub-$5 AI Plus offering in India later that year.

Google’s latest decision brings that pricing strategy to the United States, where subscription costs have so far played a smaller role in competition between major AI companies.

The development could increase pressure on competitors, particularly Anthropic, which has not introduced a lower-cost subscription tier or localised pricing in key international markets.

OpenAI and Anthropic are both preparing for public listings after filing confidential IPO paperwork, and growing price competition could become an important issue for investors assessing the long-term profitability of AI businesses.

The new markets are Australia, Indonesia, Japan, the Philippines, Singapore, South Korea and Vietnam, with the rollout covering desktop and iOS in all listed countries except Japan, where it is currently limited to desktop users.

Gemini in Chrome first launched in the United States in January, after which Google extended access to India, Canada and New Zealand in March. With this latest expansion, more users can now use the feature directly inside the Chrome browser.

Google has been adding more Gemini tools to Chrome since last year. The assistant appears in a floating window and can help users with tasks while they browse.

Earlier this year, Google also introduced a sidebar version that can answer questions across multiple tabs. It can summarise long pages, compare information from open tabs and respond without users leaving the browser.

The feature also works with several Google services. Users can schedule meetings through Calendar, check places with Maps, and draft or send emails through Gmail.

Google’s Personal Intelligence feature is also available through Gemini in Chrome. It allows users to connect services such as Gmail and Google Photos to receive more personalised responses.

Users can also ask questions about YouTube videos while staying on the same page.

Another tool, Nano Banana 2, lets users edit or transform images on the web using text prompts in the Chrome sidebar.

Some advanced functions are still limited to the United States. Google said its agentic feature, which can control a browser window and complete tasks for users, is still being tested.

That feature is only available to subscribers on the AI Pro and AI Ultra paid plans in the U.S. for now.

Within that surge, the drive between Google and Microsoft has become one to pull focus on, not just for technology leadership, but for how artificial intelligence (AI) turns into profitable business, especially with committed spending.

Two Companies, Two Directions

Even before you look deeper, you’d notice both companies are building similar systems, but you’d see the difference in how those systems are used.

Google is pushing its models into products people already use every day, including Search, Android, and YouTube. Its Gemini platform has crossed 750 million monthly users, giving it reach that few competitors can match.

Microsoft is taking a different route which is more structured. Its Copilot tools are built into Word, Excel, Teams and other workplace software. The idea is to make businesses pay for productivity.

That difference is where we place our attention. Google has scale, while Microsoft has pricing.

The Competition is Infrastructure

It is easy to focus on apps and chat interfaces, but that is not where the case is being decided.

It is in infrastructure you’d find the competition; data centres, chips, and computing power.

Alphabet, Google’s parent company, plans to spend $175 billion to $185 billion in 2026 alone, largely on servers, networking and AI capacity.

Microsoft is also increasing spending, with its capital expenditure expected to move towards $100 billion or more, driven by demand for cloud and AI services.

This level of investment changes the nature of the industry. AI is not just software, it is capital-intensive, closer to energy or telecoms than traditional tech.

I would put it this way, whoever controls compute, controls the market.

Products: Gemini vs Copilot

The difference in strategy becomes better to grasp at the product level.

Google’s Gemini is built for wide use, sitting inside search results, mobile devices and developer tools. Updates have been frequent, with new versions released through 2025 and early 2026 to improve reasoning and performance.

Microsoft’s Copilot is more targeted, focusing on workplace tasks, writing documents, analysing spreadsheets, and summarising meetings.

But adoption?

Microsoft has around 15 million paid Copilot users, a small share of its Microsoft 365 base of hundreds of millions.

That gap stresses the fact that interest in AI tools is high. Paying for them is still limited.

Cloud: Where the Money Actually Comes From

The revenue engine is behind the scenes. Google Cloud has been expanding, with revenue growth close to 48% year-on-year, driven largely by demand for AI workloads.

Microsoft Azure is however a larger business, with strong growth tied directly to AI usage and enterprise demand.

This is where the competition becomes tougher because companies are not just using AI tools, they are renting computing power to run them.

Cloud turns AI into something billable.

Spending is Increasing Faster Than Returns

There is, nonetheless, an imbalance.

Microsoft is targeting $25 billion in AI-related revenue by 2026, supported by Copilot and Azure services.

Google is already seeing profits in advertising and cloud from its AI rollout.

But both are spending far ahead of what they are earning.

Even within Microsoft’s ecosystem, only a small percentage of users are paying for AI features, despite heavy investment and promotion.

So when does this start paying off?

It is Important to note that Investors are not ignoring the risk.

Google’s decision to increase spending has already triggered mixed reactions in the market, even as its core business stands strong.

Microsoft is facing a different issue, which is adoption. Copilot is growing, but not at a pace that fully justifies the scale of investment yet.

So the market is in a strange position, believing in the long-term potential, but watching the short-term numbers carefully.

Here the Bigger Question Comes

This has gone beyond a competition between two companies. Will the current level of investment produce the kind of productivity being promised?

The comparison with past technology cycles is unavoidable. Large amounts of capital are being deployed ahead of proven returns. That does not automatically mean a bubble, but it does introduce risk.

Right now, demand for computing power is strong, but what we don’t know is whether that demand will remain strong enough to justify the infrastructure being built.

Who is Ahead?

The answer depends on how you measure it.

Google is ahead when it comes to reach. Its products touch billions of users, and its AI systems are already embedded into everyday digital activity.

Microsoft comes top in structure. It has a clearer path to monetisation through enterprise software and cloud services.

Google and Microsoft are strong when it comes to AI, both are spending heavily, but neither has fully solved the same problem, which is turning scale into sustained profit.

So, let’s not look at who builds the better model between Google and Microsoft or who comes top in AI spending, but who can turn artificial intelligence into a reliable business before the cost of building it becomes harder to justify.

That is where this growth will be decided.

The agreement, announced on Monday, hands Google a function inside Apple’s ecosystem at a moment when Apple has had issues trying to scale in advanced software development. 

Under the deal, Google Gemini models will power the upcoming version of Siri and extend into other features tied to Apple Intelligence, a clear transition away from Apple’s tradition of relying almost entirely on its own tools.

Gemini already underpins key features in Samsung’s Galaxy devices, but Apple’s reach is much larger. With more than two billion active devices worldwide, Apple offers Google access to a scale that few platforms can match.

“After careful evaluation, Apple determined Google’s AI technology provides the most capable foundation for Apple Foundation Models,” Google said, adding that Gemini will support future Apple Intelligence features as well.

While neither company disclosed financial terms, industry reports put the deal at roughly $1 billion per year. If accurate, it would rank among the largest licensing agreements of its kind and underline how urgent Apple’s position has become. 

Gemini 3, Google’s latest flagship model, reportedly runs on about 1.2 trillion parameters. Apple’s internal models are believed to be far smaller, a gap that helps explain why Apple looked outside after repeated delays.

Those delays have been expensive. Since mid-2024, Apple has pushed back major improvements to Siri several times. Executive reshuffles followed, and the first wave of Apple’s generative tools failed to impress users or developers. 

Apple had already opened the door to outside help late last year by integrating ChatGPT into its devices. That arrangement allowed Siri to hand off complex questions to the chatbot, but only if users opted in. 

The new setup changes the balance. Gemini will sit much closer to the core of Apple’s system, while ChatGPT remains a secondary option.

“Apple’s decision to use Google’s Gemini models for Siri shifts OpenAI into a more supporting role, with ChatGPT remaining positioned for complex, opt-in queries rather than the default intelligence layer,” said Parth Talsania, CEO of Equisights Research.

However, Tesla chief executive Elon Musk wrote on X: “This seems like an unreasonable concentration of power for Google, given that (they) also have Android and Chrome.” Musk runs his own firm, xAI, which is investing heavily to compete with the biggest players.

Beyond the technology itself, the deal strengthens a commercial relationship that has lasted for years. Google already pays Apple tens of billions of dollars annually to remain the default search engine on iPhones and other devices.

Adding Gemini tightens that bond and makes Google even more embedded in Apple’s daily operations.

Investors welcomed the news. Alphabet’s market value climbed above $4 trillion on Monday, placing it in a small club alongside Nvidia, Microsoft and Apple itself. The company’s shares rose 65% last year, driven by growing trust in its strategy and speedy progress across text, image and video systems.

Google also moved quickly to address issues around data use. “Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple’s industry-leading privacy standards,” the company said.

At CES 2026 in Las Vegas, the company revealed new Gemini features for Google TV that go beyond content search, aiming to change how people interact with their screens entirely.

Instead of scrolling through menus or adjusting settings mid-show, viewers will soon be able to speak to their TV in plain language. 

You can ask for recommendations that suit more than one person, request a recap of a series you missed, or describe a film without knowing its title. 

Gemini is built to respond like a conversation, not a command list. If you forget a show’s name but remember the plot or an actor, that’s enough.

Google demonstrated this with everyday questions, including, “What’s the new hospital drama everyone’s talking about?” The response is not just text. Gemini uses a visual layout that changes based on the question, mixing words, images, video context and live sports data when needed. The idea is to make the TV screen useful, not cluttered.

The company is starting this rollout with TCL, its launch partner for Gemini on TV. The features will first appear on TCL’s flagship QM9K series before expanding to other Google TV devices in the coming months. 

That is important because Google TV and Android TV OS already run on more than 300 million monthly active devices worldwide, including televisions, streaming boxes and projectors. This gives Gemini instant scale once the wider rollout begins.

Entertainment is only part of the plan. Google wants the TV to double as a learning tool. When users ask a question they want to understand, the screen can present a guided overview of the topic. 

Concepts are broken down visually, with narration, and follow-up questions can be asked without restarting the search. It feels closer to a lesson than a lookup.

Personal media is also getting attention. Gemini can search through Google Photos on the TV, helping users find specific people or moments. It can apply artistic styles to photos and videos and turn them into cinematic slideshows.

Google believes that people want to relive memories on a larger screen, not just a phone.

One of the most practical changes is how Gemini handles TV settings. If the picture looks wrong or the sound is unclear, there’s no need to pause and hunt through menus. 

Saying things like “the screen is too dim” or “I can’t hear the dialogue” prompts Gemini to adjust the right controls instantly, without pulling you out of what you’re watching.

All of this depends on software. The new features require devices running Android TV OS 14 or higher and an active internet connection. OS 14, which began rolling out widely in 2025, brought upgrades such as picture-in-picture, improved energy-saving modes, smoother performance and stronger accessibility and security features. 

A Google account is also required, and support will vary by language, country and device at launch.

Strategically, Google is no longer treating the TV as a passive screen. With Gemini, it is positioning the television as an always-on home hub, capable of conversation, learning and control. 

In that process, Gemini is also stepping into the role once held by the older Google Assistant, promising more natural dialogue and bigger abilities.

Less visible are the strategists who determine how those breakthroughs become products that millions of people can actually use.

Taslim Okunola is one of those strategists.

At Google, where the competition to lead the next phase of artificial intelligence has intensified, Okunola works as a Global Strategy and Operations Manager, helping design the operational systems behind some of the company’s most ambitious AI offerings.

From the San Francisco Bay Area, he works on the frameworks that support subscription-based services connected to Google’s Gemini ecosystem, helping shape how advanced AI capabilities are packaged, priced and delivered to global users.

“The real challenge in technology isn’t only building powerful tools. It’s figuring out how those tools become sustainable products that people can rely on every day,” Okunola said.

His journey to Silicon Valley began at the Federal University of Technology, Akure, known widely as FUTA, where he studied Agricultural Technology.

The degree focused heavily on agricultural and resource economics, a field centred on efficiency, incentives and large-scale systems.

Those principles, he says, turned out to be unexpectedly relevant in the technology industry.

“Economics trains you to think about concepts like scale of preference and opportunity costs. When you’re working on global technology platforms, you’re constantly making trade-offs about resources, priorities and scale,” he said.

Okunola entered the technology sector through digital marketing, beginning his career as an intern in Nigeria during a period when Africa’s digital economy was expanding rapidly. Smartphones were spreading quickly, internet access was improving, and global technology companies were beginning to tailor their products to emerging markets.

When he joined Google, he found himself working on exactly that challenge.

As Product Marketing Manager for Consumer Apps in Sub-Saharan Africa, Okunola helped shape how millions of people across the region interacted with Google’s products.

His work included helping introduce Nigerian English voice recognition for Google Assistant and supporting localisation efforts across tools like Google Maps.

For Okunola, those projects were about more than technology.

“If a product doesn’t feel familiar, people don’t trust it,” he said. “Localisation is not just translation. It’s understanding how people actually live and making the technology they use in their everyday routines relatable.”

The experience gave him an unusual vantage point within the company, balancing global technology strategy with the realities of emerging markets.

It also sharpened his ability to operate in environments where uncertainty is common and systems must be built quickly.

Today, those skills are being applied to one of the most consequential shifts in the modern technology industry: the rise of artificial intelligence.

Across Silicon Valley, companies are racing to embed AI into everything from search engines and productivity software to mobile operating systems.

Yet building sophisticated models is only part of the challenge. Transforming those models into reliable businesses requires operational structure, including pricing strategies, marketing coordination, resource planning and global distribution.

That is where Okunola’s work comes in.

He helps design the operational architecture behind Google’s AI subscriptions, including bundled services such as Gemini and NotebookLM.

These frameworks guide how AI features are introduced to users, how marketing teams coordinate across regions and how resources are allocated across enormous global portfolios.

“In large organisations, innovation can slow down if the structure isn’t clear,” Okunola said. “Our job is to create systems that allow teams to move quickly without losing alignment,” he added.

Much of that work happens behind the scenes. Okunola helps coordinate business planning for portfolios tied to billions of dollars in spending and contributes to marketing structures involving hundreds of employees.

The role is essentially strategy execution at scale, making sure product ambition translates into real user growth and sustainable revenue.

Earlier in his career, Okunola demonstrated a similar focus on efficiency and structure. He has led annual planning processes for Google’s Platforms and Ecosystems Marketing group, which includes major products such as Android, Chrome, Google Photos and Google TV, helping determine where investments would have the greatest impact.

His career also reflects a broader trend shaping the global technology workforce. Increasingly, professionals from emerging markets are influencing how the world’s largest digital platforms operate.

Over the past decade, Okunola’s work has spanned Africa, North America and Europe, giving him insight into how technology products evolve across different economic environments and cultural contexts.

That perspective may become even more important as artificial intelligence becomes embedded in everyday digital life.

AI may be developed in specialised research labs, but its success ultimately depends on how effectively it reaches people across languages, cultures and markets.

From the lecture halls of FUTA to strategy meetings in Silicon Valley, Taslim Okunola has built a career around that challenge by designing the operational blueprints that turn powerful technologies into tools used by millions.

This new model is designed to help everyone, from casual creators to global enterprises, turn their ideas into high-fidelity visuals with unprecedented control.

Just as the original Nano Banana model empowered everyday creativity, Nano Banana Pro represents a leap forward, blending state-of-the-art AI reasoning with creative precision.

“Nano Banana Pro is the best model for creating images with correctly rendered and legible text directly in the image, whether you’re looking for a short tagline, or a long paragraph,” said Naina Raisinghani, product manager at Google DeepMind.

The launch of Nano Banana Pro is especially exciting for creators and students in Nigeria, where the interest in AI tools is surging.

Search interest in ‘AI for studying,’ for example, has jumped by over 200% in the last year, demonstrating a strong desire to use AI for academic growth. Furthermore, ‘AI for graphic design’ is one of the top trending AI search queries, underscoring the demand for professional creative tools.

Nano Banana Pro is uniquely positioned to meet this demand, offering the perfect solution for Nigerian users who are learning new skills, creating content, and looking for AI that can deliver both factual accuracy and high-quality visual results.

Creativity Meets Intelligence

Nano Banana Pro brings four major enhancements to the creation process:

Factual Visuals and Infographics: Thanks to its foundation in Gemini 3, Nano Banana Pro connects to Google Search’s vast knowledge base.

This means it doesn’t just generate beautiful images; it creates context-rich, helpful content. Users can now generate accurate infographics, diagrams, or visualize real-time information like recipes and sports data.

Generate Legible Text in Images: A common challenge in AI imaging is garbled text, but Nano Banana Pro solves this.

It is the best model for creating images with correctly rendered and legible text directly in the image, supporting multiple languages. This unlocks new possibilities for designers creating posters, mockups, and campaigns that require precise typography.

Blend Multiple Elements for Consistent Scenes: For complex scenes or branding, Nano Banana Pro allows users to blend more elements than ever before, using up to 14 reference images to maintain consistent style, branding, and character likeness across entire compositions.

This bridges the gap between concept and production-ready assets.

Advanced Photo Editing and Control: For precise control, the model offers advanced localized editing features. Users can fine-tune images by adjusting camera angles, focus, and scene lighting (like changing day to night), with final outputs available in high-resolution 2K and 4K for any platform.

Committed to Transparency

Google is also expanding its commitment to transparency with new tools for verification. Google believes it is critical to know when an image is AI-generated:

• New Verification Tool: Users can now upload any image into the Gemini app and simply ask if it was generated by Google AI, thanks to our embedded, imperceptible SynthID digital watermark.

• Watermark Policy Update: To support professional creators, Google is removing the visible watermark (the Gemini sparkle) from images generated by Google AI Ultra tier subscribers in the Gemini app, while still keeping the invisible SynthID watermark active.

Availability of Nano Banana Pro

Nano Banana Pro is rolling out globally already across Google’s ecosystem. Consumers can access it in the Gemini app by selecting the ‘Thinking’ model, with Google AI Plus, Pro, and Ultra subscribers receiving higher usage quotas.

For businesses, it is available in Google Ads, Google Slides, and Vids, and accessible to developers through the Gemini API and Vertex AI for scaled creation.

The agreement, according to Bloomberg, would be one of Apple’s biggest collaborations with an external technology partner in years.

For now, Apple plans to rely on Google’s large-scale model, which has 1.2 trillion parameters, to strengthen Siri’s processing power and decision-making. 

That’s nearly eight times more advanced than Apple’s current 150 billion-parameter cloud model. The company sees the deal as a temporary measure while it works to bring its own artificial intelligence system up to par.

Apple tested several models, including OpenAI’s ChatGPT and Anthropic’s Claude, before selecting Google’s Gemini earlier this year. Those close to the project said Apple concluded that Gemini offered the best blend of speed, reliability, and contextual understanding.

The revamped Siri, codenamed Linwood, is expected to launch next spring as part of iOS 26.4. The project, known internally as Glenwood, is being overseen by Mike Rockwell, the executive behind the Vision Pro headset, and software engineering chief Craig Federighi.

Under the terms being finalised, Google’s Gemini model will manage Siri’s “summariser” and “planner” functions, which help the assistant interpret user intent and coordinate complex actions. 

However, Apple’s own models will still handle several on-device tasks. To protect user data, Gemini will operate within Apple’s Private Cloud Compute servers rather than Google’s infrastructure.

Neither company has commented publicly on the partnership. Unlike the Safari search deal, Apple is expected to keep Google’s role behind the scenes, branding Siri’s improvements under its own ecosystem rather than sharing credit.

The collaboration is a rare moment of pragmatism from Apple, which has long avoided outsourcing key software capabilities. But as competitors like OpenAI, Microsoft, and Google grow quickly, Apple appears more willing to depend on outside systems, at least for now, to maintain competitiveness.

Despite leaning on Google, Apple has not abandoned its vision to build proprietary AI tools. The company’s in-house models team is reportedly developing a trillion-parameter cloud model, aiming to match Gemini’s quality by next year. Executives say they can phase out the Google technology in due course.

Globally, Apple is also preparing a version of the new Siri for the Chinese market, where Google services are banned. The Chinese variant is expected to run entirely on Apple’s own models with a compliance layer from Alibaba Group, tailored to meet local regulatory demands.

Shares of both companies briefly rose after reports of the talks surfaced, Apple gaining less than 1% to $271.70, and Alphabet rising as much as 3.2% to $286.42.

Coming under the country’s new digital markets regime aimed at curbing monopoly and ensuring fairer competition, the decision follows months of investigation and consultation involving more than 80 stakeholders, including direct engagement with Google. 

According to the CMA, Google’s market position in the UK is “substantial and entrenched,” with the company commanding more than 90% of all search queries conducted in the country.

Will Hayter, executive director for Digital Markets at the CMA, said: “By promoting competition in digital markets like search and search advertising we can unlock opportunities for businesses big and small to support innovation and growth, driving investment across the UK economy. We have found that Google maintains a strategic position in the search and search advertising sector – with more than 90% of searches in the UK taking place on its platform.”

The designation does not amount to a finding of wrongdoing, nor does it impose immediate obligations. However, it grants the CMA the legal authority to enforce targeted decisions when necessary, including measures to enhance transparency and open access in the digital search market.

Under the new framework, which came into effect on January 1, 2025, the CMA has powers to issue binding conduct requirements and penalties for non-compliance. These measures are designed to ensure that technology firms operating in the UK do not exploit their market monopoly to the detriment of competitors and consumers.

In June, the regulator had outlined potential steps such as ensuring fairer search result rankings and offering users greater access to alternative search engines. It also clarified that Google’s AI-based features, including AI Mode and AI Overviews, fall within the scope of this designation, though its Gemini AI assistant is excluded for now, with its status to be reviewed as the market evolves.

Responding to the CMA’s decision, Oliver Bethell, Google’s senior director for Competition, spoke on the potential impact on innovation:

“Many of the ideas for interventions that have been raised in this process would inhibit UK innovation and growth, potentially slowing product launches at a time of profound AI-based innovation.”

The CMA, however, insists its approach will remain “targeted and proportionate,” aiming to drive innovation while ensuring fair play in digital markets. The regulator is expected to consult on specific interventions later this year.

The announcement came from the General Services Administration (GSA) on Tuesday, confirming that the three AI platforms have been added to the government’s Multiple Award Schedule. 

This change removes the need for agencies to negotiate individual contracts, enabling faster integration of AI into tasks ranging from grant review and tax fraud detection to public comment analysis.

The decision is part of an AI Action Plan unveiled on 23 July, outlining 90 measures intended to strengthen U.S. drive in artificial intelligence. The plan focuses on deregulation, rapid infrastructure expansion, and aggressive AI exports to allied nations. 

It also includes fast-tracked approvals for data centre construction, expanded energy access, and the promotion of an “American AI Technology Stack”, encompassing chips, models, and industry standards.

“This is a fight that will define the 21st century,” President Donald Trump declared, framing the initiative as both a technological and geopolitical contest with China.

The new American AI Exports Programme, jointly managed by the Commerce and State Departments, will coordinate full-stack AI deployments abroad, a move that stands in contrast to the Biden administration’s more guarded approach. 

Under President Joe Biden, export restrictions on high-end AI chips and stringent safeguards on federal AI use were introduced, including measures against misinformation, consumer risks, and discriminatory impacts. Those requirements have now been rolled back.

Instead, the GSA says federal agencies will focus on AI tools “that prioritise truthfulness, accuracy, transparency, and freedom from ideological bias.” The Trump administration has also issued an executive order titled Preventing Woke AI in the Federal Government, directing agencies to avoid models deemed politically biased.

The change represents a complete reorientation of how the U.S. government intends to build, deploy, and export AI. For technology companies, it opens the door to lucrative federal contracts. 

For federal agencies, it changes the scope and speed of AI adoption, for international partners, it points to Washington being prepared to use its AI capabilities as a diplomatic and strategic tool.