One of the biggest mistakes companies make with AI is assuming rollout alone creates adoption. In reality, even strong tools can sit unused if employees do not feel involved, do not see personal upside, or are unsure how AI fits into their day-to-day work. That is the key takeaway from Fast Company’s coverage of KPMG’s new “AI Spark Innovation” program, which rewards employees for building AI use cases that can improve internal workflows or client work.
According to the article, KPMG’s U.S. advisory division is offering cash prizes for employees who demonstrate standout AI innovation, with payouts described as materially larger than typical end-of-year variable compensation awards. The goal is not just more experimentation, but a shift in culture away from measuring success only through billable hours and toward scalable innovation.
That idea matters well beyond consulting. For businesses investing in AI CRM, AI SDR workflows, AI lead generation, and AI lead conversion, adoption often fails not because the technology is weak, but because the people using it never become active participants in the rollout. If employees view AI as something imposed on them, usage stays shallow. If they help shape the workflows, the odds of long-term success rise sharply. This is an inference based on the article’s discussion of employee input and Krazimo’s core implementation focus.
Why KPMG’s Approach Is Worth Paying Attention To
Fast Company quotes Akhil Verghese calling KPMG’s move “a brilliant move,” arguing that leaders who want employees to embrace AI should actively involve them in generating ideas. His point is that this makes employees part of the company’s AI adoption journey rather than passive recipients of top-down change.
That is a strong framing for enterprise AI. In many organizations, the hardest part is not finding a model or buying software. It is creating real behavioral change across teams. Incentives help because they do two things at once: they surface practical use cases from the people closest to the work, and they reduce fear by making experimentation feel rewarded rather than threatening.
This also aligns with a broader workforce trend mentioned in the article. Fast Company cites a 2025 Lightcast study saying jobs mentioning at least one AI skill offered salaries 28% higher, while jobs mentioning two AI skills offered salaries 43% higher. The article also cites a 2025 Kyndryl report saying 45% of CEOs believe employees are actively resistant to AI. Together, those two points explain why companies are under pressure to build AI-literate teams instead of merely purchasing AI tools.
What This Means for AI CRM and AI SDR Rollouts
For customer-facing systems, the lesson is especially important. A company can deploy an AI CRM, an AI sales assistant, or an automated lead qualification workflow, but if the sales team or operations team does not trust the outputs, they will work around the system instead of through it. That leads to poor data quality, weak follow-up discipline, and disappointing ROI. This application is an inference, but it follows directly from the article’s adoption logic and Krazimo’s existing focus on AI CRM and revenue workflows.
The smarter approach is to treat adoption as part of the product itself. That means identifying real workflow pain points, inviting employees to propose improvements, rewarding practical wins, and using early experiments to build confidence. In that sense, KPMG’s incentive model is not really about prizes. It is about creating the kind of workforce that can actually absorb AI into production.
Verghese makes a related point in the article: many early AI deployments fail because the technology is still maturing, and the most valuable part of these early efforts may be less about immediate results and more about building an AI-literate employee base. That is an especially useful lens for companies deciding whether early experiments are “worth it.” Sometimes the near-term payoff is not just efficiency. It is capability-building inside the organization.
Final Thoughts
KPMG’s program is a useful reminder that successful AI adoption is not purely a technical challenge. It is a people challenge, an incentives challenge, and a workflow design challenge. Businesses that want better outcomes from AI automation, AI CRM, AI SDR, and related systems should think seriously about how they make employees feel ownership over the process, not just compliance with it.
You can read the full original Fast Company article here.
