AI + People Power

The secret to unlocking AI in enterprises is to focus on where it can deliver the biggest benefits in employee productivity and customer experience. As leaders, we need to acknowledge that our employees and developers are ready to embrace AI and its benefits at a pace faster than we are enabling. 

We can – and should – harness this “people power” to fuel progress on AI. Our people want to solve challenges that every one of us already face in business – answering those universal questions like ‘I want answers to my questions faster’ or ‘I want a way that makes it easier to resolve issues’ and ‘I don’t want to follow ten steps in the process when I know there’s a better way do it’. And they’re ready to create those solutions with AI – if their leaders let them do so.

The most effective AI strategy channels this people power. It fits the problems our employees are already trying to solve by applying AI to the specific role-based tasks (what we call use cases) of their everyday work. AI and GenAI tools cannot replace the years of experience an individual has honed throughout their career. But it can supercharge an employee’s expertise – and also, if done at scale, the development of entire economies. 

A new spin on skilling

When ServiceNow first launched its Hyderabad office, our mailroom team was using spreadsheets and emails to coordinate notifications about incoming couriers. The trouble with this was how easily someone could miss time-sensitive notifications for critical couriers – like those carrying banking, legal, or compliance documents, which need to be delivered to the named recipients within a certain time frame. That prompted Hanumanta, one of our Workplace Services managers, to build an app using ServiceNow that automated the entire process, from updating the mail database to sending notifications within predefined SLAs. 

It took Hanumanta, a non-coder, just 3 months to build the app – all the way from design to security and user testing. Now, the app is being used in 16 ServiceNow offices worldwide, saving each an average of 20 hours a month and greatly reducing the risks (and headaches) associated with manual mail tracking.

All this is to say that those who best understand the problem often prove most equipped to author its solution: they are their own customers.

Skilled individuals from non-technology disciplines, like Hanumanta, possess something that most professional developers lack: the domain expertise to understand and solve the most pressing problems their industries face. When equipped with tools like low-code and generative AI, individuals can then directly create applications that tackle challenges they are already familiar with, without nuances getting “lost in translation” between them and a professional developer. 

At ServiceNow we have already employed this approach to promising effect, hiring our product managers out of industry specific disciplines ranging from retail to finance and ESG. The expertise that these people bring to our team helps us develop solutions that are far more in-tune with the needs of the industries they came from. This has proven particularly valuable in developing smaller, “domain-focused” generative AI models that understand the unique language, processes, and practices of complex industries. These product managers may not be as well-versed in the “how” of building software, but they understand the “what” and “why” more keenly than just about anyone.

A common playbook for problem solvers

Technology is no longer a separate stream of study or profession. It has become a layer across every discipline. Ideally, our approach to education and training will increasingly reflect this by incorporating core digital skills at every stage of learning. More immediately, we can broaden our definition of tech talent beyond computer scientists and developers to include digital-savvy experts from all manner of other fields; and lower the technical barriers to digital innovation for them as much as possible in the tools and workflows we employ. Hanumanta’s example shows the good that can happen when we democratise AI and other technologies in the workplace, rather than unnecessarily gatekeeping them.

Leaders would do well to focus on hiring and cultivating problem-solvers – those with skills in strategic thinking, analytical creativity, and communication. These problem-solvers are distinct from “doers” who may be technically proficient in executing tasks; but struggle to see beyond the status quo and seek ways to do things better, for greater value. Notably, such skills can come from a far broader variety of disciplines than IT and engineering: fields like the arts, mathematics, and sciences all hold significant untapped potential. That also gives leaders in Asia Pacific a prime opportunity to bypass the region’s endemic IT skills shortages if they can at once hire problem-solvers from these non-conventional fields; and train and equip them to solve business problems at speed using GenAI.

This approach may very well transform how we tackle our biggest national challenges. It puts tools for digital innovation in the hands of the scientists, doctors, and other experts whose work directly impacts the nation’s welfare. And it empowers them to solve pressing challenges faster, more creatively, than ever before.

By bringing more experts from a wider range of domains into the digital innovation field, we would not only fill many of the gaps in tech skills today. We would also ignite growth across all manner of industries and, perhaps most importantly, make greater inroads on major socioeconomic issues. Cultivating this diverse team of digital talent will help us win more often both at home and on the world stage.