The Self-Driving Enterprise: How AI Will Make Apps and Us Work Better
AI has begun to take hold in the everyday, in the form of Siri, Alexa and autonomous vehicles. But if identifying the nearest Korean BBQ and driving me there is all that the future of AI promises, well that’s a damn shame.
It’s time that we become a lot more ambitious about the future of AI. There’s a broad perception that the best that AI has to offer will be in the consumer world. This is not the case, and it demonstrates a severe lack of imagination. So, while some may pine for a robot assistant to appear in their favorite retail store, the most impactful applications of AI will actually be where we work.
Consider how the healthcare industry might be transformed by AI. We can empower doctors and nurses to focus on what matters: providing care. CRM-like applications will assist doctors to prescribe personalized treatment plans based on patient history, the latest research and optimized clinical pathways. Payers’ systems will automatically evaluate the vast majority of clinical procedure requests, freeing caregivers from managing claims approvals, and accelerating treatments and prioritizing human intervention on the most complex cases. Care-focused apps will help physicians make prescription decisions, and smart devices will administer those medicines, accounting for a patient’s history, minute-to-minute diagnostics and best practices. High-touch apps will enable primary caregivers and patients to collaborate during recovery, proactively recommending personalized steps and monitoring progress. Making a healthcare moon shot a reality has a lot to do with how the industry will efficiently leverage the vast amounts of data now at its disposal, and that’s going to take some serious AI.
But we don’t need to rip and replace to get there. Whatever the industry, we can take advantage of AI by making our current work tools — apps, medical devices, supply chain systems — much better through machine learning. Many of us have seen how infusing AI into existing systems and devices can automate thousands of routine tasks and drive improved decision making for complex ones. Done right, we can embed AI into essentially every business process.
The key is in the delivery — in other words, the “operationalization” of the analytics. Smart apps need both to influence behavior and provide seamless interaction between humans and machines. In most cases, we won’t — and shouldn’t — even notice the presence of AI. In others, we should collaborate with machines via a clean hand-off that’s appropriate for the context.
The self-driving car is a great analogy for AI-enabled apps. The best autonomous vehicle systems will surely be able to handle the driving task in typical conditions; there are lots of little decisions to be made, but they are straightforward and easy. It’s when conditions become more challenging that the magic happens; the car will not only know when a human should intervene, but also will smoothly transfer control to the driver and then back to the machine.
But in today’s enterprise, we’re nowhere near that kind of seamless AI–human connection.
