December 1, 2025 Why Perfect Practice Will Shape the Winners of 2026

To win with AI in 2026, companies must master the fundamentals. Strong data, clear governance and solid change management drive results.

By Michael Simms

If you’ve ever been a competitive athlete at any level, you’ve probably heard that “practice makes perfect,” but that isn’t exactly true. Perfect practice makes perfect. If you’re practicing to improve without first refining your basic skills, you’ll be building on a wobbly foundation. Getting the fundamentals right is the critical first step of developing any skill — as well as the critical first step when pursuing AI initiatives.

With AI, the concept is the same: If you’re trying to improve without mastering the basics, you’re most likely going to be sorely disappointed with the results. AI innovation will only deliver lasting business value if companies refocus on core fundamentals like data quality, governance and change management rather than chasing flashy tools and hype.

Focus on the foundation

Since ChatGPT’s groundbreaking debut in late 2022, the buzz around GenAI hasn’t stopped. However, this hype cycle led many organizations to rush into deploying AI tools without first having the necessary infrastructure to support these systems. As a result, many of these projects have failed to hit ROI and performance targets. In fact, 70–85% of GenAI projects fail to meet expectations — and expectations are high. Organizations that effectively execute AI projects report remarkable improvements in productivity and business impact, but achieving that hinges on proper preparation.

To avoid falling victim to the “shiny object syndrome” that has plagued many enterprises’ AI plans, the first step is to practice a little patience. Rome wasn’t built in a day, and neither was any successful AI system. Thoughtful implementation is the key to achieving the desired returns on AI investments, and that starts with laying the groundwork prior to pushing out new tech. To avoid a half-baked and wholly unsuccessful AI strategy, focus on the following first:

After years of experimentation, 2026 will be the end of the AI pilot phase. Companies must show demonstrable ROI or risk being left behind by competitors. Organizations that focus on the fundamentals before implementation will overtake those who adopted tools first without addressing the underlying readiness. Fundamentals-first organizations will be effectively scaling AI across departments. Tools-first organizations will be bombarded with stumbling blocks around data quality, integration challenges and organizational resistance that will keep them from moving past isolated use cases.

In the end, championship-winning teams in both sports and business are those that master the basics first. The truth is that fundamentals aren’t glamorous, but they are the key to winning games. In 2026 and beyond, the organizations that resisted skipping foundational steps will see the most success. In AI, as in sports, there are no shortcuts to excellence.

About the Author
Michael Simms is the Vice President of Data & AI at Columbus, and is a seasoned technical manager who has been developing data and artificial intelligence solutions for nearly three decades. He has been at the leading edge of AI, Data, ERP and other emerging technologies. He plays a principal role in architecting and implementing projects from creation through go-live. Simms also excels at creating and supporting offerings in the analytics/digital transformation space, specifically for Gen AI, machine learning, and data science. His extensive expertise includes data architecture, data migration, data engineering, and AI.

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