The AI Opportunity Lies in Customization, Not Just Buying More Software

A former Microsoft engineering leader and founder of his own data and AI consulting firm has a clear vision for the future of artificial intelligence. Rob Collie spent 13 years at Microsoft, where he was one of the founding engineers behind Power BI, a platform that helps clients visualize data and infuse insights into other Microsoft apps. He’s now written a book about organizational AI strategy called ‘Fair Game,’ which will be published on August 11.

After years of studying how companies approach AI, Collie has come to a stark conclusion: most businesses are doing it wrong. They’re not just buying more AI-powered software or rushing to build their own large language models; they’re trying to use these tools without adapting them to their specific needs and workflows. This is the ‘shallow end’ of AI adoption, according to Collie.

The problem with off-the-shelf AI solutions is that they don’t automatically understand a company’s internal processes, strategy, or institutional knowledge. They need context, which can be provided by connecting them to business data, workflows, and software. This approach allows companies to generate significant returns without having to train their own models from scratch.

Collie likens commercial large language models (LLMs) to Lego bricks: they’re powerful tools that can be combined in various ways to create something new and useful. However, instead of building a new model, businesses should focus on customizing existing ones by feeding them the right context at the right time. This is where the real opportunity lies.

But who are the people best suited to lead this effort? Collie identifies ‘crafters’ as key players in AI adoption. These individuals are not necessarily software developers or data professionals but rather problem-solvers embedded within businesses. They’re often responsible for automating tedious work, creating dashboards, and writing scripts – tasks that require a deep understanding of the company’s operations.

Collie estimates that about 1 in 16 people fit this ‘crafter’ profile, which is more than the number of professional software developers. These individuals are not limited by their technical skills; AI can now help them write real software and tackle complex problems that IT teams never had time for. By combining these crafters with AI tools, businesses can unlock significant value.

When looking for AI leaders, Collie suggests asking questions like ‘Who’s the Excel guru?’ or ‘Who keeps inventing clever solutions to make the business run?’ These individuals are already thinking like builders and have a deep understanding of their company’s operations. They’re not necessarily experts in AI but know how to use it effectively.

Collie also emphasizes that companies shouldn’t wait for a top-down AI strategy before getting started. Organizations operate on thousands of individual workflows, which cannot be redesigned from headquarters alone. Successful businesses will start with small customization wins close to the business and learn from those successes as they expand their efforts.

In conclusion, Collie’s vision for AI adoption is centered around customization and empowering crafters within organizations. By focusing on adapting existing models to specific needs and workflows, companies can unlock significant returns without having to build their own large language models from scratch.