“There’s no magic answer” as CIOs remain pressured to roll out AI and deliver results

“Every CIO is under pressure from their management and board to roll out AI and deliver results. And there's no magic answer for all,” says Shannon Bell, Executive Vice President, Chief Digital Officer, and Chief Information Officer at OpenText.

CIOs are now feeling the pressure to roll out AI and deliver results as business leaders began looking for the ROI from all their AI investments. In her conversation with customers, Shannon Bell, Executive Vice President, Chief Digital Officer, and Chief Information Officer at OpenText shared that apart from sharing use cases, business processes and experiences, she can see that CIOs are looking for help and support in their AI journey.

For Bell, the best way OpenText is to help deal with these challenges is by sharing their own journey with AI as customer zero. Bell explained that by sharing their own AI journey, they are enabling customers to understand, see the value and metrics not only of what they are delivering but also what they have failed to make customers understand.

“We've been building what we call the agentic genome. When we started our agentic deployment, we mapped our entire organization. We went function by function and job by job of our 1,700 different job titles across 21,000 plus employees. We looked at each and every role and we looked at what the human in the role should do and what agentic AI could do in this situation. And then, we mapped those roles into the end-to-end business processes that drive our organization. So standard processes like hiring to retire from an HR perspective, procure to pay, lead to cash, and all the standard business processes that we have,” Bell explained.

“So, we mapped roles, we mapped agentic and human capabilities, we mapped out our business processes. And that was how we started to identify which processes we wanted to go after implementing agentic AI. And now, we've been bringing that to our customers because 80% of it is common. Even if you're in the pharmaceutical industry or financial services, 20% of it will be unique to your industry. And so it's really helping our customers with a fast track to what an agentic enterprise deployment looks like and how they can drive those capabilities,” she added.

Helping customers understand the AI journey

Looking at customers in Singapore, Bell highlighted that while there is overwhelmingly a strong drive for AI with some of the government mandates around driving digital transformation and adoption, businesses in the country are certainly feeling the pressure from their leadership.

“They're starting to move towards agentic AI, but there's concern about how quickly they'll see the results. And so, there's a little bit of a mismatch in terms of expectations of outcomes and results and the length of time that it takes. So we've been discussing strategies for driving outcomes and how to properly build the foundations. Now the thing I would say, and what I heard loud and clear, is there's not going to be time to deliver a complete data overhaul or transformation of all business processes,” added Bell.

Specifically, Bell believes that the efforts to adopt AI have to be focused on specific use cases or rather specific business processes. These can then be incrementally addressed across the enterprise for other use cases.

“No organization today is going to wait for a big bang business process transformation. And so they're going to have to do it at the same time as they're starting to adopt AI. But all of that took place in under two years. And so, we were driving results incrementally and showing the value. And I think that's the pragmatic approach I'm hearing CIOs want to take,” Bell said.

At the same time, Bell believes that while businesses need to show results and the value of AI, they should also be investing in the foundational building blocks of AI.

“If you think of an agentic AI deployment, you can't start with your most complicated business process. You need to start with simple use cases and then look at how you orchestrate those together in a flow,” she said.

An example Bell shared was how businesses can look at the impact of legacy systems. This includes looking at how businesses can manage agentic flows on legacy systems which again are not going to go away anytime soon and are pervasive in the financial services industry.

“I think pragmatic strategies to start incrementally build value and set expectations with organizations that truly autonomous agentic AI is key. There will be humans in the loop for probably the next 12 months and to get to fully autonomous you want to be a hundred percent certain that you're able to deliver consistent results before you actually move to fully autonomous,” she concluded.