Corporate AI strategies often begin the same way. Buy the tools. Train employees. Measure adoption. Hope productivity follows.
Newgen Software believes the sequence is backwards.
“We don’t measure AI success by the number of employees trained,” says Kashish Kapoor, the company’s global chief human resources officer. “We measure it by how naturally AI becomes part of everyday work.”
The distinction is important. Teaching employees how to use AI is relatively easy. Redesigning work so that people and AI genuinely complement one another is much harder. It requires organisations to rethink hiring, learning, performance management and leadership together rather than treating them as separate initiatives.
The company argues that AI creates value only when people, processes and technology evolve in parallel. Whether that integrated approach delivers a lasting advantage remains to be seen. But it moves the conversation beyond AI literacy towards organisational redesign.
Hiring for adaptability
Newgen has shifted its hiring philosophy away from recruiting people with narrowly defined technical expertise.
“Today, we hire less for what someone knows and more for how quickly they can learn, adapt and create value,” Kapoor says
“We don’t measure AI success by the number of employees trained. We measure it by how naturally AI becomes part of everyday work.”
Kashish Kapoor, Global CHRO, Newgen Software
That philosophy has become increasingly common across the technology sector. The real challenge lies in supporting it after recruitment.
Hiring for potential works only if organisations invest continuously in developing that potential.
Newgen attempts to do that through personalised learning journeys, AI labs, hackathons and cross-functional mobility. It is also placing greater emphasis on business understanding alongside technical capability. As the company increasingly positions itself as an enterprise performance partner rather than simply a software provider, employees are expected to understand customer problems as well as technology.
The objective is no longer to produce better engineers alone, but professionals capable of connecting technology with business outcomes.
Learning through work
Many AI learning programmes still rely on classroom sessions and mandatory certification.
Newgen has chosen a different route.
Instead of treating AI as another subject employees need to study, it encourages them to use AI while building products, solving customer problems, improving internal operations and supporting sales teams.
“The biggest shift is moving from a change programme to a learning culture,” Kapoor says.
The distinction matters because change programmes eventually end. Learning cultures do not.
The company points to growing cross-functional collaboration, wider AI adoption and increased employee mobility as indicators that the approach is gaining traction. While those outcomes are difficult to verify independently, the underlying philosophy is clear: employees learn AI fastest when it becomes part of their everyday work rather than an occasional training exercise.
Redefining performance
Newgen is also changing how performance is evaluated.
Alongside traditional business outcomes, the company increasingly rewards behaviours such as collaboration, innovation, continuous learning and responsible AI use.
The last element reflects the company’s customer base. Banks, insurers and government agencies operate in highly regulated environments where AI decisions often carry legal, financial and ethical consequences.
Employees are therefore encouraged to ask not only whether AI can perform a task, but whether it should.
As AI capabilities become easier to access, judgement may become a greater competitive advantage than technical proficiency alone.
Managing human-AI teams
Kapoor believes leadership expectations are changing just as quickly.
Managers increasingly need to decide which work belongs with people, which belongs with AI, and which requires both.
That demands different capabilities from traditional people management.
Accordingly, Newgen measures AI readiness less through training completion and more through business outcomes. It looks at how employees apply AI in customer engagements, how quickly they acquire new capabilities, productivity improvements and the value delivered to clients.
Measuring outcomes instead of activity is a more demanding approach. It also avoids a common trap where organisations confuse course completion with genuine capability.
Beyond AI training
Newgen’s approach is notable because it treats AI as an organisational challenge rather than a technology initiative.
Hiring, learning, leadership and performance are designed to reinforce one another instead of evolving independently.
That is considerably harder than launching an AI training programme. It requires sustained changes across multiple people systems at the same time.
That integration is also the hardest part to sustain. Competing priorities, budget cycles and leadership changes all create pressure to revert to simpler, more measurable interventions.
As AI tools become widely available, access to technology is unlikely to distinguish one software company from another. The bigger differentiator may be how effectively organisations redesign themselves around it.