Despite the growing prevalence of AI technology, getting value from AI isn’t easy. 40% of organizations making significant investments in AI still do not report business gains from AI. As with technology advances in the past, technology alone isn’t the answer to value.
Getting value from AI requires investment beyond technology, notably in data infrastructure and talent. Once armed with technology and infrastructure, many organizations find that they don’t have the AI skills they need. Technology creates an inevitable gap — a gap between the sophisticated solutions an organization produces with a given technology.
As organizations put more resources into a general-purpose technology such as AI, they can produce more sophisticated results with the technology. For example, customer churn models can boost prediction through more sophisticated algorithms. Fraud detection can better discern legitimate from nefarious transactions. All of these applications benefit significantly from recent improvements in AI.
Few people produce AI models themselves. Most employees are consumers of the results of those models. Consumption is necessary because technologies like AI do not work in vacuums. Technology requires business context — which is organization-specific. This context is more difficult to outsource.
Because improvements in consumption increase more slowly than advances in production, the gap between what an organization can produce and consume can increase rather than decrease. Ironically, as the organization matures, it faces a growing gap. Organizations must therefore encourage employees to use their new skills.
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