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AI and automation: Business leaders adopt small-scale solutions for greater impact

Business leaders recognize automation is changing the way companies operate. The hope is that automation — whether it’s in the form of robots, machine learning, or artificial intelligence (AI) — will make us all more productive in the not-so-distant future.

However, getting to the point where automation enhances our working life is far from straightforward. Despite the cacophonous hype associated with AI during the past year, experts suggest emerging technologies must be explored in a careful and considerate manner.

Also: Generative AI and machine learning are engineering the future in these 9 disciplines

That’s certainly the approach being taken by Sasha Jory, CIO at insurer Hastings Direct. While her team is investigating “all sorts of different things” in automation, she says they’ve already learned a valuable lesson from their explorations.

We’ve entered a period of dramatic innovation in AI and automation and it’s going to have a significant impact on the future of jobs, productivity, and the ways we operate in teams. Research predicts that worker productivity could increase by as much as 4x by 2030, powered by AI. We unpack the opportunities and the ways to benefit from this transformation.

“One of the things we’ve found with automation is that if a process is broken and doesn’t work today, then automating that process just makes the mess go faster,” she says.

Avoiding that nightmare scenario means taking a tactical approach to automation. “We choose carefully where we think that we can make a difference,” says Jory. “A lot of our automation is about removing manual processes, bringing in streamlining, creating opportunities through robotics to do processes, and teaching the technology to do things that previously a human being would have done.”

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Rather than a big-bang approach that relies on a huge investment in enterprise-wide services, such as robotic process automation (RPA), Jory and her team search for small-scale opportunities.

That’s a big shift from a few years ago when the IT industry was abuzz with the potential of RPA, which uses software robots or AI agents to perform repetitive tasks that might once have been pursued by humans.

Adobe CIO Cynthia Stoddard, for example, described in an interview for ZDNET in 2021 how her organization embraced RPA.

The technology giant has worked with UiPath to create a Centre of Excellence for RPA, which manages the building, tooling, and implementation of the automation platform across Adobe, as well as the automation of business processes.

Stoddard says the successful use of RPA in finance helped sponsor the wider adoption of the technology across the business, producing big boosts in productivity.

Also: As developers learn the ins and outs of generative AI, non-developers will follow

However, not every business is able to spend a large amount of money and effort building an enterprise-wide approach to automation — and that’s a sentiment that resonates with Jory at Hastings.

“We’re not pursuing big, large-scale process automation, because that is time-consuming and can often be very difficult,” she says. “Our approach is all about picking small things where we can make a difference.”

Evidence suggests Jory might not be the only digital leader who’s looking at small-scale ways to automate processes.

While Gartner says spending on RPA software reached $2.8 billion in 2022, up from $2.3 billion in 2021, annual growth in the RPA market has slowed during the past few years from 62% in 2019 to 22% in 2022.

Also: What technology analysts are saying about the future of generative AI

Nash Squared’s recently released Digital Leadership Report also shows growth in RPA is making slow progress; the proportion of CIOs who say their organizations have large-scale RPA implementations has crept up from 10% to 12% this year.

A few years ago, RPA might have been the only way to take advantage of automation in a strategic manner. Now, other technologies are available, recognizes Bev White, CEO at Nash Squared, and using those small-scale solutions might be more appropriate than a big-bang approach.

“RPA can be really a fantastic game-changer in certain industries for wholescale processing of massive piles of data that needs dealing with,” she says. “At the same time, I don’t think it’s for everyone. RPA is one of those things that came out with great aplomb. It’s got its fans; it’s delivered some fantastic returns on investment. But it’s now one of many things CIOs can consider — and it’s not always the right thing. There are other ways of embracing automation that could be more productive.”

Also: How trusted generative AI can improve the connected customer experience

In short, if you’re a digital or a business leader with a limited budget, you don’t always have to invest in a large-scale RPA project, White told ZDNET — especially now that other tools, including robotics, generative AI, and machine learning, are available.

“Well, that’s the point,” she says. “And dipping a toe into AI isn’t as expensive. You can run three or four small projects to test out different elements and still have a decent amount of change left in your pocket.”

That’s certainly the case at Hastings, where Jory gives an example of how the company uses automation in its IT processes to ensure everything runs smoothly with as little human intervention as possible.

“If a messaging queue got stuck in the past, then somebody would go in and remove a message and push the queue forward,” she says. “Now, we’ve got technology that will go in and identify the queue is stuck, and the message that is holding it back. It will remove the message, it will alert the team, and then the queue will carry on running.”

Jory says the IT team is also using observability, which provides visibility into Hastings’ applications stack and allows for the automated identification and resolution of problems.

Also: How to achieve hyper-personalization using generative AI platforms

“It’s massively important to be able to see what’s going on in our systems all of the time,” she says. “We used to have lots of hung threads that required a server restart — and now those just restart automatically. But we also have logic in there, so we don’t do restarts in the middle of the day at the busiest time, which would then cause issues for our colleagues.”

In the future, Jory expects a combination of generative AI and machine learning to form part of the organization’s tactical approach to automation. The insurer receives a lot of documents and photographic evidence of accidents. Emerging technology could help to automate the checking and verification of this data.

“Instead of having to trawl through all of that evidence, whether it’s a handwritten document, a photograph or an email or whatever, it’s about being able to take that information and to create a summary of what’s going on for the customer,” Jory said. AI and machine learning could also be used in fraud-detection processes: “Are there certain behaviors we can see in our data that we might want to follow up on?”

Similarly to CIOs at other organizations, Jory says Hastings is currently considering its options when it comes to generative AI. The company is working with its key core IT providers, including Microsoft, EY, and Snowflake. The internal IT team is also exploring how it might build AI-focused tools with these partners.

Also: Generative AI and the fourth why: Building trust with your customer

Whether it’s dabbling in generative AI or implementing machine learning and robotics, Jory advises other executives to take a careful and considered approach to automation.

“I’d say start small — find obvious places to go,” she says. “Don’t go into big, hefty business processes and think you will be able to suddenly automate everything. Be focused, be clear on what you choose, and get the scores on the door quickly, so people buy into your strategy, and you can get more momentum.”

Original Article: AI and automation: Business leaders adopt small-scale solutions for greater impact (msn.com)

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