Business leaders recognize that automation is change the way businesses operate. The hope is that automation — whether 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 improves our working lives is far from simple. Despite the cacophonous hype associated with AI over the past year, experts suggest that emerging technologies need to be explored carefully and thoughtfully.
Also: Generative AI and machine learning are shaping the future in these 9 disciplines
This is certainly the approach taken by Sasha Jory, CIO at insurer Hastings Direct. While her team studies “all kinds of different things” when it comes to automation, she says they’ve already learned a valuable lesson from their explorations.
“One of the things we’ve discovered with automation is that if a process is broken and isn’t working today, automating that process just accelerates the mess,” she says.
To avoid this nightmare scenario, you need to take a tactical approach to automation. “We carefully choose the areas where we think we can make a difference,” says Jory. “A lot of our automation is about removing manual processes, streamlining, creating opportunities through robotics to do processes and teaching technology to do things that a human being would have done before.”
Also: Generative AI is everything, everywhere, at once
Rather than a big-bang approach that relies on massive investment in enterprise-wide services, such as robotic process automation (RPA), Jory and his team are looking for small-scale opportunities.
This is a sea change from a few years ago, when the IT industry was buzzing about the potential of RPA, which uses software robots or AI agents to perform repetitive tasks that could once have been performed by humans.
Cynthia Stoddard, CIO of Adobe, for example, described in a interview for ZDNET in 2021 how his organization adopted RPA.
The tech giant worked with UiPath to create a Center of Excellence for RPA, which manages the creation, tooling and implementation of the automation platform within Adobe, as well as the automation business processes.
Stoddard says the successful use of RPA in the financial sector has helped drive broader adoption of the technology across the business, producing significant productivity gains.
Also: As developers learn the ins and outs of generative AI, non-developers will follow
However, not every company is able to dedicate a lot of money and effort to building an enterprise-wide approach to automation – and it’s a sentiment that resonates with Jory at Hastings.
“We’re not looking to automate processes on a large scale because it takes time and can often be very difficult,” she says. “Our approach is to choose small things where we can make a difference.”
The data suggests that Jory may not be the only digital leader looking for small-scale ways to automate processes.
While Gartner says RPA software spending reached $2.8 billion in 2022, compared to $2.3 billion in 2021, the annual growth of the RPA market has slowed in recent years, from 62% in 2019 to 22% in 2022.
Also: What tech analysts are saying about the future of generative AI
Nash Squared was recently released Digital Leadership Report also shows that RPA growth is progressing slowly; The proportion of CIOs who say their organization has implemented RPA at scale increased from 10% to 12% this year.
A few years ago, RPA might have been the only way to leverage automation strategically. Today, other technologies are available, acknowledges Bev White, CEO of Nash Squared, and using these small-scale solutions may be more appropriate than a big-bang approach.
“RPA can be a real game changer in some industries for large-scale processing of huge amounts of data that needs to be processed,” she says. “At the same time, I don’t think it’s for everyone. RPA is one of those things that was launched with a lot of aplomb. It has its fans; it has generated fantastic returns on investment. But it’s now one of many things CIOs can think about – and it’s not always the right thing. There are other ways to adopt automation that might be more productive.
Also: How Trusted Generative AI Can Improve the Connected Customer Experience
In short, if you’re a digital leader or a company 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, notably robotics, Generative AIand machine learning, are available.
“Well, that’s the point,” she said. “And getting started with AI doesn’t cost as much. You can run three or four small projects to test different things and still have a decent amount of change in your pocket.”
This is certainly the case at Hastings, where Jory gives an example of how the company uses automation of its IT processes to ensure everything runs smoothly with as little human intervention as possible.
“If a messaging queue was stuck in the past, someone would come in, delete a message and move the queue forward,” she says. “Now we have technology that will identify the blocked queue and the message that’s holding it up. It will delete the message, alert the team, and then the queue will continue to run.”
Jory explains that the IT team also uses observability, which provides visibility into Hastings’ application stack and enables automated problem identification and resolution.
Also: How to Achieve Hyper-Personalization Using Generative AI Platforms
“It’s extremely important to be able to see what’s happening in our systems at any time,” she says. “We used to have a lot of blocked threads that required a server restart – and now those 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 problems for our colleagues.
Going forward, Jory expects a combination of generative AI and machine learning to be part of the organization’s tactical approach to automation. The insurer receives numerous documents and photographic evidence of accidents. Emerging technologies could help automate the verification and verification of this data.
“Instead of having to go through all this evidence, whether it’s a handwritten document, a photograph, an email or whatever, it’s about being able to take that information and create a summary of what’s happening 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 track? »
Similar to CIOs of other organizations, Jory says Hastings is currently considering its options for generative AI. The company works with its major IT vendors, including Microsoft, EY and Snowflake. The internal IT team is also exploring how it could build AI-focused tools with these partners.
Also: Generative AI and the fourth why: building trust with your customer
Whether embarking on generative AI or implementing machine learning and robotics, Jory advises other leaders to take a careful and thoughtful approach to automation.
“I would say start small – find obvious places to go,” she says. “Don’t go into large, cumbersome business processes thinking you’ll suddenly be able to automate everything. Be focused, be clear about what you choose and get the scores quickly, so people buy into your strategy, and you can grow bigger.
