Organizations in this group are moving now on AI in a systematic, potentially slower manner than headfirst enthusiasts. They only invest in use cases that will meaningfully impact their overall strategy instead of seeking out the most interesting AI use cases. By 2030, these organizations will have realized significant benefits from their AI investments. Depending on the organization and their strategic goals, benefits could appear as improved outcomes, reduced costs, faster drug development, more engaged patients or members, and/or more support for their workforce.
Every organization should be striving to be in that third group, but today many are falling into one of the first two groups, where they’re moving too slowly or too fast. So, what do organizations need to do to move to the third group and guarantee long-term AI success?
The first, and most impactful change, is to realize that you should not have an AI strategy. Rather, AI should enable your existing strategy. That is to say, the best AI strategy is not about AI — it’s about you and your organization. This key distinction is what keeps organizations from getting caught up in the hype or investing in technologies that are “nice to have” instead of “need to have.”
You should also consider how AI can evolve your strategy over time, specifically looking at healthcare challenges or goals previously considered unsolvable or unattainable. This mindset allows you to creatively apply new capabilities while staying focused on specific needs, such as mitigating the workforce shortage, closing care gaps, and improving health equity.
The second change organizations need to make is to assess your pace of adoption in the face of potential pitfalls and challenges. You will want to avoid moving too quickly as this can lead you to ignore AI pitfalls such as bias. At the same time, you don’t want to allow pitfalls, or hesitancy around challenges, to slow you down.
Organizations can only find a balanced pace and mitigate risks if they are willing to meet challenges head on. Instead of letting a fear of bias or errors keep you from investing, let it drive your approach to investing. Watch and learn from the successes and failures of early adopters. Take the time to build internal processes and staff expertise that will help solve these challenges for your organization. And you should consider your partnerships as well, revamping your processes for choosing a partner to make sure they have a similar approach to tackling these challenges.