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Many surveys and much of the available research shows about a 50/50 split between companies that understand how to apply artificial intelligence (AI) technology to their businesses versus those that do not. So, looking at those who understand how to use AI is a good place to start.
These companies — I will call them AI Actives — have long since addressed the “how-to” question and continue to advance. Market leaders, even those that experience dips and bounces in financial performance, already invested in data and analytics as difference makers. The other 50 percent — I will call AI Hopefuls — have data, software and people who support it all, but have yet to execute and scale use cases beyond trials, at most.
Some AI Actives have begun reporting a lack of success and disappointing results. What sometimes happens is that, despite human capital, advanced technology and lots of data, the use cases selected may not be right or were not scoped and executed correctly. Many times the company’s strategy for AI doesn’t align the right resources with the proper use cases.
AI can actually be simple and easy because it is a feature, a function or the purpose of almost anything technology-related today.
Hopefuls aware of these options might feel relief knowing there is a fast path to AI that differs from the slog endeavored by AI Actives.
The lesson here is that, regardless of whether you are an Active or a Hopeful, success depends on:
- Identifying the use cases most relevant to your business and prioritizing them.
- Aligning the right resources to the right use cases.
- Continually re-evaluating use case opportunities for relevance and prioritization.