Monthly insights into human-AI collaboration – and how to make it work for your teams.
Our ongoing series brings you essential AI news and takeaways every month, helping you stay informed and ready for what’s next in the world of artificial intelligence.
September 2025 edition
How AI is revolutionizing the C-suite
Founders and CEOs have been among the most enthusiastic adopters of generative AI in their organizations, wooed by the technology’s potential to maximize output by automating various tasks. Now, many top executives are beginning to realize that AI is more than just a workforce efficiency booster – it can also supercharge their capacity as leaders.
The big picture: CEOs embrace AI assistants
In an IBM survey of 2,000 global CEOs, 61% of executives said that they have adopted AI agents in their own workflows and are preparing for large-scale deployment across their organizations. Some top leaders, such as Weber Shandwick North America CEO, Jim O’Leary, are even using AI to scale themselves. O’Leary told Fast Company that he saves one to two hours each workday by using AI tools to draft communications in his style and streamline workflows. Similarly, Nvidia’s Jensen Huang has reported using AI as a “tutor” to help him master new concepts and skillsets, while Apple CEO Tim Cook uses it to summarize long emails.
Going one step further, the futurist Michael Tchong predicts that an age of AI “co-CEOs” could be on the horizon. Tchong, who has spent the last four decades analyzing the interplay of tech and business, recently told Business Insider that executives without AI assistants may soon be written off as “corporately deficient” in the way they’re running their operations. Some companies are even experimenting with AI-powered CEOs, though preliminary research indicates that human leaders still outperform bots.
The takeaway: AI co-pilots are driving an evolution in leadership
As AI continues to absorb leadership tasks such as executive communication, data analysis, and organizational strategy, CEOs will need to rethink the way they approach their daily workflows and design short- and long-term priorities. It will become ever more critical to home in on the strategic goals and big-picture thinking that yield meaningful innovation. In other words, leaders will have to double down on the human side of being in charge.
Try this
- Implement one AI tool as a daily helper. Choose a single, secure tool and use it for a few repeat jobs (summarizing long threads, taking live notes, drafting team updates).
- Decide faster with one-page briefs. For major decisions, use AI to generate a one-pager with options, risks, and recommendations.
- Try small, then scale. Run a short-term test – say, 30 days – using AI to streamline executive workflows. Keep what works (and onboard your team to new processes), and drop what doesn’t.
How AI is powering research and development
Across industries – from packaged foods to pharmaceuticals – companies are turning to AI to shave years from their research and development (R&D) timespans. The economic implications are no joke: In a new report, McKinsey predicts that AI is poised to double the pace of R&D, adding up to half a trillion dollars in value per year.
The big picture: Turning AI-driven insight into innovation
While generative AI is often touted as a tool for boosting organizational efficiency, McKinsey points out that the technology can also be a powerful lever for innovation. By handling information-intensive tasks and accelerating knowledge synthesis, generative AI lets teams come up with new ideas more quickly. AI can also create digital stand-ins that predict how well a potential new product or process will work, circumventing the need to build and test prototypes.
Individual case studies support McKinsey’s premise. In a roundtable discussion hosted by the Federal Reserve Bank of San Francisco, several executives said that they already use generative AI to assess client insights, which helps them pinpoint product solutions more quickly. In a similar vein, a new survey from the marketing strategy and insights firm GBK Collective found that nearly half of market researchers are already using AI to analyze transcripts and consumer data, laying the groundwork to make better, faster decisions.
The takeaway: A more level playing field
In the age of generative AI, traditional R&D bottlenecks like limited ideation and expensive validation no longer pose a barrier to innovation. While this is good news for companies of every size, it’s especially promising for smaller enterprises with leaner R&D budgets looking to compete on a broader scale.
Try this
- Widen the idea funnel. Use AI to scan papers, customer signals, and past experiments, then brainstorm lots of options quickly.
- Test onscreen before in the lab. Lean on simulations and AI-designed test plans, and only build when ideas meet a clear threshold.
- Measure and protect your work. Track time to first prototype, cost per experiment, and success rates. Be sure to keep a record of the you fed the AI and what it produced, with dates and links – this is so you can prove ownership and show that your results came from approved sources for audits and IP.