Automate it: How businesses are streamlining their operations

Computing research sheds a light onto UK IT leaders’ automation efforts

Part two of Computing’s latest research into the priorities of UK IT leaders.

Automation is the foundation of digitisation, and organisations of all types have been quietly getting on with streamlining operations using machine learning, AI, RPA and BPA for years, away from the glare of generative AI. GenAI is starting to make its presence felt too, but as we saw in a previous article, its impact has not yet measured up to the column inches dedicated to it.

So what are organisations automating and how are they going about it?

According to a Computing survey of 100 UK IT leaders the primary focus, by some distance, is automating cybersecurity.

In many ways, cybersecurity is the ideal candidate for the application of AI/ML, given the vast amounts of data that must be processed 24/7; the need for rapid, probability-based decision-making and near-real-time data analytics; and the ability to identify patterns and anomalies that are imperceptible to human operators. Defensive actions are also being automated as a first line of defence, and generative AI is contributing by creating realistic cyberattack simulations, generating synthetic datasets and scenarios, and detecting phishing attempts.

Thus far, AI seems to more useful to defenders than to attackers - although this advantage may not endure, of course.

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Business process automation (BPA) and the automation of back-office processes with RPA - mainstays in the transition from paper-strewn silos to smoothly integrated services - were another key focus for many respondents.

Software development and deployment have long been the subject of automation efforts, from smart IDEs to Kubernetes, and many developers are excited by new generative tools and agents that can suggest new approaches as well as automating boilerplate tasks. However, others emphasise the importance of having experienced developers on hand to ensure errors in generated code are identified before they proliferate.

A frequent goal for sales is hyper-personalisation, with AI assisting in the creation of one-to-one communications based on previous behaviour and preferences. Predictive analytics, pipeline analysis and enhanced customer engagement are increasingly being handed off to machines too.

Customer support is often considered the low-hanging fruit of automation and it’s already one of the most familiar applications from the point of view of the general public, with chatbots now a familiar part of everyday life. Familiar, but not necessarily loved. Not for nothing has the word Clanker – meaning malfunctioning robot – re-entered the vernacular.

Cost-cutting bosses at Klarna, Commonwealth Bank of Australia, Taco Bell and MacDonalds have all rowed back on their AI ambitions after their chatbots went rogue or in some other way delivered a ‘suboptimal customer experience’ – such as bacon-topped ice cream. People, it turns out, like to talk to other people. And they don’t like bacon on ice cream.

Which is not to say GenAI is vapourware, even if it’s valuation may be way out of kilter with current realities. There are plenty of examples of well planned and well implemented AI projects where the right tools have been selected for the job which are already yielding impressive results.

Examples offered by our respondents include:

IT leaders interested in automating cyber won’t want to miss the Computing Security Leaders Summit on March 26th 2026. Packed with content including AI/ML, bridging the cyber skills gap and cloud resilience, its promises to be full of insight and practical advice to take away. Register here for your free place.