Prakash Kota wants artificial intelligence to change the work surrounding a customer conversation before that conversation begins. His vision is an assistant that recognizes an upcoming meeting, gathers relevant information and prepares an employee without waiting for a prompt. Getting there, however, requires decisions about business processes and enterprise data that precede the choice of an AI tool.

As UKG’s newly promoted chief transformation officer, Kota is expanding that approach across a roughly $5 billion revenue provider of HR, payroll and workforce management solutions serving more than 80,000 organizations. His mandate builds on approximately 18 months as CIO. “The mandate is make sure our strategy, our process, our data, tech and talent are all moving in the same direction,” he explained.

Building a Common Foundation

UKG was formed through the combination of Ultimate Software and Kronos in 2020. When Kota arrived, complexity in the supporting systems and processes was limiting the company’s ability to scale. His initial priorities included consolidating customer relationship management systems, enterprise resource planning platforms and data environments, alongside centralizing the technology function.

The work addressed a problem that often gets obscured by enthusiasm for new capabilities: different functions could be making decisions from different information. Kota wanted sales, finance and customer experience teams working from a shared foundation. “Whether the news is good or not good, you’re at least looking at the same data and marching towards solving the same problem,” he noted.

After making substantial progress on those foundations, he is turning to broader process transformation. A software engineer by background, Kota acknowledged that earlier in his career he sometimes deployed attractive technologies before identifying a problem they could solve. He now begins with the work, the desired outcome and the points where a process slows down, bringing technology choices into the discussion afterward.

Connecting the Customer Journey

That approach has shaped UKG’s modernization of the journey from initial prospect engagement to becoming a customer. Previously, Kota described an experience involving successive departmental handoffs, with employees repeatedly researching the same prospect before they could contribute. The objective was to carry relevant information through the process so each interaction could build on the last.

AI now helps qualify and prioritize leads before they reach business development or sales teams. Employees receive context and signals alongside the lead, reducing the preparation required to begin a useful conversation. “Now, through this journey of the flow, all of that intelligence and signal and connectivity goes along so there is a lot of continuity to the conversation,” Kota said.

The standard for success extends beyond completing an activity faster. Kota looks at decision quality, customer experience and the ability to scale with less complexity. He cautioned that accelerating a flawed process can simply move the organization faster in the wrong direction. The relevant question is whether a change helps employees serve customers more effectively, rather than how much AI they use.

Designing AI Assistants Around Human Expertise

Kota’s next ambition, part of an initiative called Rewired, is to make AI assistance more proactive. He sees a limitation in the proliferation of conversational tools: employees still need to know what to ask, assemble the results and determine what to do next. His proposed alternative is an assistant that anticipates the information required for a particular role or activity.

For a salesperson, that could mean receiving a meeting briefing automatically, preserving time for the relationship and the decisions that emerge from it. “It’s more about building relationship, getting into a dialogue, and making decisions,” Kota emphasized. He sees those activities as the contribution of a human expert, while an assistant could handle much of the information gathering and preparation.

The approach remains a development agenda, with Kota describing ambitions for the following 18 months. To progress, he uses a launch, learn and land framework: put a defined use case in the hands of early testers, study what works and correct shortcomings, then establish that it fits the workflow and meets standards before expanding. That sequence creates room for experimentation without requiring an enterprise-wide deployment at the outset.

Making Transformation a Shared Responsibility

Kota’s expanded title does not make transformation the responsibility of one office. He described a leadership model that connects cross-functional programs to common company goals, asking how each initiative affects customers and employees. “It cannot be all divisional goals marching in silos,” he underscored. Shared measures and ownership help translate that agreement into execution.

CEO Jennifer Morgan reinforces the approach through a weekly review of the company’s top 10 programs. Program leaders participate in a dashboard-driven discussion of business measures and progress. When an initiative falls behind, Kota described the response as assembling the people needed to help, rather than assigning blame. That makes teams more willing to disclose problems before they become harder to resolve.

“Setting goals is one aspect, and then following through to ensure that execution also is a big rigor,” Kota reflected. For UKG, the next stage of AI depends on maintaining that connection between business priorities and daily work, with the systems, processes and leadership attention needed to turn experimentation into a better customer and employee experience.

Peter High is President of Metis Strategy, a business and IT advisory firm. He has written three bestselling books, including his latest Getting to Nimble. He also moderates the Technovation podcast series and speaks at conferences around the world. Follow him on Twitter @PeterAHigh.