Why AI Fizzles, and How Smart CEOs Can Get it Back on Track

By now, most CEOs have taken at least some steps toward adoption of artificial intelligence within their workforce. It may have started with a pilot program in customer service, a generative tool in marketing, or a predictive model in the supply chain. Often the push came from a board member, a vendor demo, or internal enthusiasm.

But for many midmarket companies, the early momentum has faded. The tools are technically in place, but the outcomes are unclear. Leadership teams may find themselves asking:

• Are we getting anything meaningful from this?

• Who’s tracking success? 

• Is this even tied to our business goals?

This doesn’t mean the effort has failed. Rather, it’s at a common inflection point. Early curiosity has to give way to operational alignment. That alignment requires leadership, not just experimentation.

Beware the Illusion of Progress

In many organizations, AI gets off the ground quickly. Pilots are launched, teams are engaged, and vendor activity creates visible motion. But over time, energy dissipates and measurable value is hard to find. 

McKinsey & Company’s Global Survey on the State of AI is clear on this point. It finds that companies seeing the strongest returns from AI are not just adopting tools. They are redesigning workflows, embedding AI into decision-making, and measuring impact through KPIs. In these companies, CEOs are visibly engaged in AI initiatives, not by managing the technology, but by treating AI as part of how the business operates, not a side project or innovation exercise.

3 Examples of AI Success in MidMarket Companies

For CEOs looking to understand where AI is actually delivering business value, it helps to see what others have already done. These midsize firms aren’t chasing headlines; they’re using AI to solve specific, costly business problems — and got measurable results:

• Chalo: Personalization at Scale. Chalo is a transit technology firm operating in India and other developing markets. It faced a classic growth challenge: how to better meet the diverse needs of its commuters while increasing ridership. By applying machine learning to ridership data, Chalo created 72 “Super Saver” monthly pass options tailored to specific rider behavior. This level of personalization would have been impossible without AI. The impact was immediate: 95% of monthly riders switched to one of the new plans, leading to a 55% jump in ridership and a 25% increase in revenue. The takeaway: AI can enable segmentation strategies that unlock growth in ways traditional pricing models cannot.

• Blendhub: Generative AI Multiplies Team Output (Without New Headcount). Blendhub is a “food-as-a-service” company based in Spain that turned to AI not to cut costs, but to scale smarter. Operating with lean teams across quality assurance (QA), marketing, and analytics, Blendhub introduced generative AI (GenAI) tools such as ChatGPT, Midjourney, and GitHub Copilot. The results were dramatic: QA and regulatory processes now run twice as fast, marketing output tripled, and data analysis is five times more efficient. Blendhub didn’t replace staff — it elevated their output. The takeaway: This is the real promise of GenAI for midmarket firms: scaling capabilities without bloating costs. 

• Ascendum: Faster Field Service with GenAI Assistants. At Ascendum, a Portugal-based distributor and servicer of heavy machinery, its field technicians were spending 30 minutes or more searching through technical manuals to diagnose problems. In 2024, Ascendum deployed a GenAI assistant integrated with Salesforce Field Service. It allowed techs to query tens of thousands of documents and receive fast, accurate repair guidance. The result? Higher first-time resolution, significantly reduced downtime, and customer savings estimated at $5,000 to $12,000 per hour of uptime regained. The takeaway: When implemented correctly, AI can enhance front-line performance and deliver meaningful ROI without increasing headcount.

What the Research Says

When companies use AI to support clearly defined goals — such as improving forecast accuracy or reducing churn — their chances of success rise significantly, said Kartik Hosanagar, a professor of operations and co-director of human-AI research in the Wharton School at the University of Pennsylvania. 

Wharton’s Strategies for Accountable AI program reinforces this idea. The program advises companies to begin AI projects by identifying the specific outcome they want to improve, then work backward to explore how AI might help. Starting with the business needs helps lead to more grounded applications and faster learning loops.

McKinsey’s research supports this view, linking the company’s strong financial results from AI to the CEO’s active involvement. That doesn’t mean CEOs are reviewing technical specs. It means they are staying engaged, asking clear questions, and ensuring AI initiatives are tied to measurable business outcomes. 

In midsize organizations, where leadership visibility carries even more weight, C-suite engagement often determines whether AI efforts move forward or stall out.

What Great CEOs Are Doing

High-performing CEOs treat AI as part of the business operating system. They do not delegate it out and hope it comes back with a business case. They stay close enough to see what’s working, where there’s friction, and what needs focus.

They begin by helping the organization sharpen its lens. Rather than approving everything that sounds innovative, they challenge their teams to identify business problems worth solving and outcomes worth improving.

They ask: 

• Where are we making decisions without good data?

• Which workflows are still driven by gut instinct?

• What parts of the business are slow or error-prone that do not need to be?

Just as importantly, these CEOs bring AI into the right rooms. AI gains traction when it shows up in operating reviews, when it’s linked to KPIs, and when it’s part of how performance is discussed. When it’s only mentioned in strategy slides or innovation sessions, it tends to fade. 

The best CEOs do not need to champion AI loudly. They show up consistently. That is what moves the work forward.

A 90-Day Reset to Get Your AI Efforts on Track

When AI efforts lose steam, it’s often due to a lack of alignment, not interest. For CEOs looking to regain momentum in their AI efforts, here is a practical structure to re-center:

Days 1-30: Take Inventory. List current AI-related efforts. Clarify their purpose, owners, and success metrics. Identify what is anchored in business outcomes and what is not.

Days 31-60: Prioritize and Recommit. Choose one or two efforts with a clear connection to your top priorities. Embed them into operating rhythms, assign senior accountability, and make expectations visible. 

Days 61-90: Formalize and Expand. Scale what is working. Establish light governance, such as a monthly check-in or dashboard. Define success criteria for expanding to other areas of the business.

Bringing It All Together

Most companies are no longer deciding whether to invest in AI. They are trying to figure out how to make it count. That responsibility falls squarely on the leadership team. Here are three takeaways to guide the path forward:

• Start with the business problem. Anchor every AI initiative in a goal the company already values.

• Stay close to the outcomes. You don’t need to understand the algorithm, but you do need to know what is working, what is not, and why. 

• Make AI part of the operating cadence. When it shows up in business reviews and is measured like any other lever, teams know it matters. 

Former Cisco CEO John Chambers offered a clear warning when he said, “AI is moving faster than the internet did, and companies that fail to move quickly enough may not survive.”

But urgency without clarity does not produce results. Your teams do not need more hype; they need direction. The opportunity is here. The tools are available. What turns AI into an advantage is leadership that knows how to focus on the effort and follow through.

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Bob Goodwin is the president of Career Club, where he works with senior executives to elevate leadership performance and align business strategy with people outcomes. He also hosts Career Club Live, a podcast featuring CHROs from leading brands, and co-hosts The Work Wire podcast alongside SHRM President and Chief Executive Officer Johnny C. Taylor, Jr., SHRM-SCP.