For CIOs and transformation leaders, the main signal here is not that GenAI is slowing down, but that it is moving from curiosity to governed investment. The management challenge is to stop treating every promising use case as a pilot and start deciding which ones merit operational funding, executive sponsorship and clear stop/go criteria. That requires explicit ownership for value, risk and adoption, not just technology delivery.
There is also a portfolio trade-off. Low-risk productivity use cases can create visible adoption and quick wins, but they rarely prove enterprise value on their own. Higher-value decision support and workflow automation may matter more to the business, yet they introduce stronger controls, better data dependencies and a longer path to benefits. The practical question is how to balance confidence-building deployments with a smaller number of more ambitious bets.
Governance should now shift from policy drafting to decision rights and measurement. Leaders need a standard for what counts as acceptable performance, where human review is mandatory, who owns model and data quality, and how exceptions are handled when GenAI behaves unpredictably. Equally important, boards should ask for benefit tracking that links use-case spend to productivity, cycle time, revenue protection or margin impact instead of generic usage statistics.
The workforce implication is just as material. If the organization signals replacement faster than it builds skills, adoption will stall and trust will erode. A stronger operating model is to pair automation plans with role redesign, training and clear communication about where humans remain accountable. Next questions: which three use cases deserve enterprise funding, what governance gates will govern them, and which metrics will prove value within the next two quarters?
GenAIโs Awkward Adolescenceย Isย Onย Full Display
Executive mandates are racing ahead of reality. Boards and CEOs often expect payback in 6โ12 months. However, disconnected strategies, messy data, and immature governance stall progress. While two-thirds of AI decision-makers say their organization uses GenAI in production, only 15% report a positive impact on earnings, and just a third can link AI spend to profit and loss. Confidence in ROI is dropping as well: In late 2024, 81% of firms reported 5% or greater ROI; by mid-2025, that fell to 62%! Without clear metrics, enterprises default to easy productivity wins that are hard to quantifyโa fragile foundation for long-term value for executives who expect to see bottom (and top) line impacts quickly.Trust Gaps and Workforce Anxietyย Are Most Concerning
Trust is still a major obstacle as the industry realizes that todayโs language models are inherently unpredictable and prone to errors, making them difficult to trust at scale. Privacy and security remain key concerns as well, with leaders anxious about data leaks and model jailbreaks. Governance for GenAI also lacks maturity. For example, 69% of AI decision-makers do not fully grasp generative AIโs nondeterminism. These gaps create a โtrust taxโ that must be paid to implement agents that use generative AI for language as a foundation. This slows down decision-making and implementation timelines. Additionally, employees are receiving mixed messages, creating confusion and disillusion. Nearly half of businesses have cut jobs due to AI and 61% anticipate some roles will disappear altogether. Yet, automation often fails to keep up in replacing these positions. At the same time, demand for AI expertise is growing rapidly, creating churn, heightening anxiety, and potentially hindering adoption.Six Broad Use Case Categories Have Emerged
The last time we wrote this report, use cases were only starting to emerge, and there were hundreds of them. By 2025 we see six broad categories evolving across three time horizons.- Now: Contentย creation, conversational assistants,ย andย software development automation. Enterprises start with low-risk, high-volume tasks like summarization, translation, and drafting marketing copy or RFPs. Conversational assistants are now common in lower risk situations. Fixing software bugs and some coding automation are also delivering benefits quickly.
- Short-term:ย Productivity/decision support andย governance automation.ย Automating work in these more critical and sensitive areas is taking longer to catch on because errors at scale can be costly.
- Mid-term: Autonomousย systems / agents.ย The great hope for language models is that they can serve as the foundation of agentic systems, but that remains to be seen for high degrees of autonomy and critical processes.
2026 Will Bringย Bubblesย Andย Batteries
The economics of GenAI have proved unforgiving. Token-based pricing clashes with early expectations of cheap AI, while longer prompts and deeper reasoning spike usage costs unpredictably. Providers are scrambling to recoup investments, but big AI tech firms are spending billions on infrastructureโAmazon plans $100 billion over the next decade, Microsoft nearly $80 billion in 2025 alone. This mismatch between costs and revenue has analysts whispering โbubble.โ And then thereโs energy: AI data centers could consume nearly 945 terawatt-hours by 2030, straining grids and budgets. . In North America, more than half the grid faces a shortage risk by 2027. Energy is now a critical resource shaping AIโs future. Battery technologies to keep energy supply flowing in support of AI demand are exploding, as are the drive to build modular nuclear reactors and microgrids.How to Work With Awkward Teenage AI
We think enterprise clients need to do three things to navigate GenAIโs early teens:- Wire every use case to a financial driver.ย Treat each deployment as a tough examโsuccess meansย a measurableย impact on profit and loss.
- Industrialize context engineering and knowledge infrastructure. Build strong habitsโ invest in AI-ready data and application context pipelines that are the foundation for reliable AI.
- Up-skill talent instead of cutting headcount.ย Invest inย AI-powered humansย and and communicate how you will bring your people along the journey.
Welcome To Jr. High, GenAI
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