Alberto Terol

🚨Once a year, the AI world gets its state of the union—and it comes from Mary Meeker.

It’s not a casual scroll-through. It’s a data-packed, insight-loaded, firehose of everything shaping the future of tech and business. When it drops, you don’t skim. You stop. You listen.

This year’s report is no exception. From breakthroughs to paradigm shifts, it’s all there.

🔍 I’ll zoom in on what matters most for leaders navigating transformation: Change Management and organizational readiness. Because riding the AI wave isn’t about tech—it’s about people, process, and mindset.

But make no mistake: the whole thing deserves your time. Trust me—you’ll want your highlighters ready.

Adoption of AI is accelerating at unprecedented speed

Artificial Intelligence is reshaping business at a pace we’ve never seen. In her May 2025 trends report on AI, renowned analyst Mary Meeker observes that rapid advances in AI, computing, and connectivity are “fundamentally reshaping how work gets done, how capital is deployed, and how leadership is defined”. This isn’t just another tech trend – it’s a transformation that will separate the prepared from the unprepared.

For business leaders, the message is clear: AI adoption is accelerating and those who act now will lead, while others risk getting left behind.

AI usage has exploded into the mainstream. Consider that ChatGPT – an AI-powered tool barely two years old – scaled to 800 million weekly active users in just 17 months. In fact, it reached its first 100 million users in only 2 months, whereas Instagram took 2.5 years and Netflix over a decade to hit the same milestone. Such breakneck growth is 5× faster than even Google’s early adoption rate, underscoring how quickly people are embracing AI-driven products.

This momentum isn’t limited to consumer apps – enterprises are jumping in as well. Fully 50% of S&P 500 companies now regularly discuss AI on their earnings calls. Industry giants from JPMorgan (banking) to Yum! Brands (hospitality) to Kaiser Permanente (healthcare) aren’t just talking – they are actively deploying AI at scale in their operations.

The ecosystem around AI is booming too: developer communities for AI platforms (like NVIDIA and Google’s AI tools) have expanded 6–7× year over-year, reflecting surging interest in building AI solutions.

👉 Bottom line: AI is no longer confined to R&D labs or tech startups – it’s being woven into everyday business processes across industries. From customer service chatbots to AI copilots in coding and content creation, organizations are finding that if they don’t leverage AI, their competitors (or even their employees) certainly will. The adoption train has left the station, and it’s picking up speed every quarter.

Massive Investment and Breakneck Technological Progress

The accelerating AI boom is fueled by equally unprecedented investment and advances in infrastructure. Companies are pouring capital into AI capabilities at record levels. The “Big Six” U.S. tech firms (Google, Amazon, Apple, Meta, Microsoft, NVIDIA) spent a staggering $212 billion on capital expenditures in 2024, a 63% jump over the prior year. This spending – largely on AI chips, data centers and cloud capacity – reflects an all-in bet on AI. It’s not just tech giants, either: worldwide, data center investments hit an all-time high of $455 billion in 2024 , driven by demand for AI and the cloud. In short, organizations are investing in the plumbing to handle AI’s intensive compute needs.

At the same time, the technology behind AI is leaping forward and becoming more efficient. For instance, NVIDIA’s latest 2024 AI chip delivers 105,000× greater energy efficiency than its 2014 GPU a mind-blowing improvement in a decade. Overall computing power for AI training has been scaling exponentially (training compute costs are up 2,400× in eight years), enabling today’s models to far outperform yesterday’s. Yet even as top-end training grows costlier, the cost of using AI (“inference”) has plummeted – down ~99% in just the past two years. In practical terms, it’s becoming dramatically cheaper to deploy AI solutions at scale, even as those solutions become more powerful.

This combination of heavy investment and rapid tech advancement means barriers to AI adoption are dropping fast. Cutting-edge AI capabilities are increasingly accessible not just to tech behemoths but to any business ready to leverage them. As Meeker’s report notes, we’re witnessing unprecedented progress on all fronts of AI – faster growth, bigger budgets, and swiftly improving hardware/software creating a perfect storm of opportunity for those prepared to ride the wave.

Preparing Your Organization for AI Adoption

Adopting AI at scale isn’t a simple software install – it requires organizational change. From reskilling your workforce to upgrading infrastructure to shifting your leadership approach, preparation is key to harness AI’s potential. To ride the AI wave, companies should focus on three areas:

• Talent Transformation: Your people are your most important AI asset. The demand for AI skilled talent is skyrocketing – U.S. job postings for AI-related roles are up 448% since 2018, even as postings for other IT roles fell by 9%. This reflects a fundamental shift: companies need data scientists, machine learning engineers, and domain experts who can work with AI. At the same time, many traditional roles will be augmented or redefined by AI. Upskilling and re-skilling programs are crucial so that existing employees can work alongside AI tools instead of being displaced by them. In Meeker’s words, tech talent must “pivot or perish” by developing AI expertise. Forward-looking firms are already encouraging every knowledge worker to become conversant in AI, ensuring that teams can leverage AI in day-to-day workflows. Action item: Invest in training, hire for AI skills, and cultivate a culture of continuous learning. Every employee should have the chance to learn how AI can amplify their work.
• Infrastructure Upgrades: AI’s power hinges on infrastructure – data, computing, and tools. Companies must assess whether their technology stack is ready for AI at scale. This might mean adopting cloud AI services, upgrading to faster GPUs or specialized AI accelerators, and ensuring data pipelines can handle the volume and quality needed for AI initiatives. Notably, major firms are already making significant investments in specialized AI hardware and cloud infrastructure to stay competitive . Even if you’re not a tech company, you may need to partner with cloud providers or invest in AI platforms to get the necessary infrastructure. Additionally, data is fuel for AI – so organizations should be building robust data ecosystems (clean data, data engineering talent, data governance) to feed their AI models. Action item: Audit your IT readiness for AI. Upgrade your computing resources (or leverage cloud AI offerings), and strengthen your data foundation. The companies that win in AI often simply have more, better, faster data and compute than others.
• Leadership & Mindset: Driving AI adoption requires clear vision and support from the top. Leaders need to champion AI as a strategic priority, not just an experimental gadget for IT. This starts with a mindset shift – embracing a bit of the startup mentality. Meeker’s report highlights how startups like OpenAI succeeded by moving fast and accepting imperfection, whereas big incumbents might have been too cautious. Corporate leaders should take note: being overly 14 3 tentative about AI (waiting for it to be “perfect” or 100% risk-free) may mean falling behind. Effective change management in this era involves setting an ambitious AI vision, encouraging calculated experimentation, and educating your workforce to ease fears. It’s also about leading by example – e.g. using AI tools in your own workflow and decisions.

👉 Action item: Ensure your leadership team deeply understands AI’s potential (and limitations). Foster an innovation-friendly culture where teams are encouraged to pilot new AI-driven ideas. Communicate a clear message that AI is integral to your company’s future – and back it with investment and personal involvement.

Lessons from Incumbents and Disruptors

Both established companies and startups offer valuable lessons on integrating AI effectively:

• Large Incumbents Adopting AI at Scale: Traditional industry leaders have shown that, with the right approach, AI can deliver concrete results today. In finance, Stripe (a major payments company) applied AI to fraud detection and instantly boosted a key fraud catch rate from 57% to 97% – an overnight improvement that would be nearly impossible without AI. And many banks, retailers, and manufacturers are rolling out AI in customer service, supply chain, and beyond. A telling indicator: half of the S&P 500 are talking about AI in earnings calls, often reporting new AI initiatives. The lesson from these incumbents is clear – those who proactively integrate AI into core business processes (with strong executive support) are cutting costs, improving outcomes, and gaining competitive edge over peers who hesitate.
• AI-Native Startups and Disruptors: On the other end, nimble startups are leveraging AI to disrupt markets and even challenge tech giants. The clearest example is OpenAI – by daring to launch ChatGPT to the public quickly (despite it occasionally “hallucinating”), it gained hundreds of millions of users and forced the rest of the industry to race to catch up. Large companies like Google likely couldn’t have launched such an imperfect AI that early, but OpenAI’s move fast mindset paid off and changed the game. Similarly, open-source AI projects are emerging at lightning speed. In 2025, a new open-source large language model called DeepSeek went from launch to capturing 21% of global LLM user share within a few months – demonstrating how quickly a disruptive AI solution can scale globally. Countless startups in fields from customer support to drug discovery are building “AI-first” business models, often out-innovating slower incumbents. The takeaway for established firms: stay agile and humble. Partner with, invest in, or learn from these upstarts – and be willing to experiment – or you could be disrupted before you know it.

The Risk of Falling Behind:

With AI advancing so fast, the cost of inaction is high. Early adopters are already seeing outsized gains. Companies integrating AI are significantly outperforming others in productivity and efficiency metrics. These advantages tend to compound over time – the more data and experience you accumulate with AI, the further ahead you can get. On the flip side, organizations that delay AI adoption risk a double whammy: missing out on current benefits and having to play catch-up in a field that’s moving at breakneck speed.

It’s not just within industries – there’s a global competitive element as well. Meeker’s report frames AI progress as a “space race” of sorts, where nations and companies that lead in AI could achieve disproportionate dominance. For instance, China has more industrial robots operating than the U.S. and the rest of the world combined – an indicator of how seriously some competitors are investing in automation and AI. If your company or country lags in AI capability, you may find others pulling away in innovation, productivity, and market share. As one analysis put it: the speed of AI innovation, talent deployment, and infrastructure built now will define who leads and who lags in the next era.

In short, the gap between AI leaders and laggards is widening. The question every business should ask isn’t “Will AI change our industry?” – that answer is yes across the board. The real question is, as Meeker says, “Will you be leading that transformation or scrambling to catch up?” . Failing to prioritize AI now is risking your organization’s relevance in the years ahead.

Call to Action: prioritize AI preparedness today

The accelerated pace of AI change means the time to act is now. Business leaders must make AI preparedness a top priority – not next year, not when regulations or standards settle, but today. That means educating yourself and your teams about AI capabilities, investing in the necessary talent and infrastructure, and championing an adaptable, innovation-friendly culture from the C-suite down. It’s okay to start small – pilot an AI project in one department, empower a cross-functional team to explore use cases – but do start. Every day of learning and experimentation builds your organization’s muscle for the AI era.

The pace of AI adoption will only accelerate. Companies that embrace this change proactively will ride the momentum to new heights; those that remain passive may find themselves irreversibly behind. As Mary Meeker’s findings suggest, we are at a pivotal moment in business history – one where AI prowess will define the next generation of industry leaders.

Are you ready? Now is the time to ensure your organization is prepared to not only adapt to this AI driven future, but to lead it. The competitive stakes are high, but so are the opportunities for those bold enough to transform. Don’t wait for “perfect” conditions – start building your AI-ready organization today, and position yourself to thrive in the amazing changes to come.

#AI #DigitalTransformation #FutureOfWork #Innovation #AgenticEnterprise