In technology services, talent is the product. Birlasoft delivers digital transformation, cloud services and enterprise technology to clients across industries, making the quality of its people a commercial differentiator rather than a support function concern. Skills are evolving faster than traditional development cycles, AI is reshaping how software is built and services are delivered, and experienced talent remains fiercely contested. In that environment, decisions about whether to build, buy or borrow capability are business decisions as much as HR decisions.
Priti Kataria led people strategy at Birlasoft through that environment. In conversation with HRKatha, she explains why the build-or-buy question has no fixed answer, why the most capable external hire often takes longer to deliver than a less polished internal one, and why the layer of the organisation most responsible for culture is also the one that receives the least investment.
Run or change: the build-or-buy question
As AI, cloud and digital engineering evolve rapidly, how do you decide what to build internally, what to hire and what to access through specialist partnerships?
This is never a single decision. I have always started with three questions: how central is the capability to what differentiates the organisation; how quickly do we need it; and how fast is the skill itself evolving?
The answer also depends on whether the organisation is in what I describe as a Run phase or a Change phase.
In a Run phase, where the business is stable and capabilities are well understood, investing in internal development makes the most sense. There is enough time to grow talent from within, and the institutional knowledge that internal development builds is genuinely valuable.
In a Change or Disrupt phase, where the organisation is transitioning to a GenAI-led delivery model or entering an entirely new capability area, the timelines are much shorter. In those situations, a mix of experienced external hiring and specialist partnerships is more appropriate.
The mix is never fixed. It changes as the business changes. What matters is recognising which phase you are actually in instead of defaulting to the approach that feels most familiar.
“Today’s mid-level managers are tomorrow’s senior leaders.”
The internal hire who delivers faster
Technology professionals often seek career acceleration by moving companies. How do you make internal mobility a meaningful alternative?
A robust internal job posting system and a genuine talent marketplace send a clear message: employees can build meaningful careers without leaving the organisation. That message, when credible, changes the retention calculation for people who might otherwise assume their only path forward is through an external move.
What undermines it most often is not the absence of policy but the presence of hoarding. When managers are not held accountable for releasing talent, when experienced employees are kept on projects because losing them creates short-term inconvenience, the internal mobility system becomes a process that exists on paper but not in practice. Employees notice quickly.
The observation I would offer from experience: a homegrown employee who is 60 to 70 per cent ready for a new role often becomes productive faster than someone hired externally at 90 per cent skill readiness. The external hire brings strong capability but still needs time to understand the organisation, its clients and its culture. The internal hire already has that context. They close the skill gap faster than the external hire closes the context gap.
Investing in internal talent delivers better long-term returns than chasing ready-made capability. It is rarely the easiest decision under pressure, which is exactly why organisations have to make it consciously.
The hardest trade-off I see organisations navigate is the tension between patience and pressure. Slower business growth and margin protection can push organisations towards external hiring decisions that feel necessary in the short term but weaken the cultural fabric over time. The right question is not whether we can afford to develop internally. It is whether we can afford not to.
“The preparation required is broader: building the habit of critical engagement with AI outputs across the entire workforce.”
Leadership readiness is enterprise risk
How confident are you that today’s high performers can become tomorrow’s leaders, and what does intentional pipeline-building actually require?
Every conscious organisation must be intentional about this because the pace of change today leaves very little margin for reactive succession.
Leadership readiness is not simply an HR initiative. It is an enterprise risk issue. When key roles become vacant and there is no pipeline, the organisation either promotes someone before they are ready or hires externally at a premium and absorbs the integration cost. Neither outcome is free.
What intentional pipeline-building actually requires is structured talent reviews, regular succession planning and continuous investment in future leaders. It means identifying high-potential talent early, tracking their development, giving cross-functional exposure, providing coaching and preparing people for roles well before vacancies arise.
Leadership pipelines do not build themselves. They require sustained investment and the discipline to prioritise long-term readiness over short-term convenience.
“The teams that innovate are rarely those where everyone thinks alike.”
Diversity beyond the obvious
What dimensions of diversity will matter most in the future, and what does the technology sector still get wrong about it?
Gender diversity will remain important. But in technology services, the diversity that most directly drives the outcomes organisations actually want, better problem-solving, stronger innovation, more relevant client solutions, is diversity of perspective.
The teams that innovate are rarely those where everyone thinks alike. The best ideas frequently come from someone who sees a problem from an entirely different angle, shaped by a different generation, a different cultural background, a different educational pathway or a different life experience.
The technology sector has historically struggled with this. It has tended to hire from a narrow set of institutions and profiles, which produces technically capable teams that are cognitively similar. That similarity feels comfortable and efficient, particularly in delivery-intensive environments where consensus is faster than debate. But it limits creativity in exactly the ways that clients increasingly need it.
Building teams that think differently from the people already in the room is rarely comfortable. It is slower, sometimes messier, and requires leaders who can draw out contributions from people who do not naturally communicate in the same way. Those are learnable skills. Most organisations have not invested enough in developing them.
“AI is no longer a technology used by a handful of specialists. It is becoming an enabler across every function.”
Every role is now an AI role
Generative AI is changing how technology services are delivered. What new capabilities are becoming indispensable, and how should organisations prepare their workforce?
The biggest shift is that AI has stopped being the preserve of specialists. It is becoming an enabler across business delivery and every business-enabling function.
In software development, developers are increasingly reviewing and refining what AI generates rather than writing every line of code themselves. The same is happening in HR: screening, scheduling, candidate follow-up and policy queries are moving steadily to AI. What this creates is more space for people to focus on judgement-intensive work.
That is why the real skill gap today is not purely technical. Every role now requires people who know what questions to ask AI, how to interpret its outputs, how to identify bias in what it recommends and when to trust or challenge what it produces. Those are not conventional technical skills. They are judgement skills that apply regardless of function or seniority.
Organisations that treat AI readiness as a technology training programme will miss this. The preparation required is broader: building the habit of critical engagement with AI outputs across the entire workforce, not just in the teams that build or deploy the technology.
“Investing in internal talent delivers better long-term returns than chasing ready-made capability.”
The layer nobody invests in enough
What is the one workforce issue the technology industry should pay far more attention to?
First-time and mid-level managers.
They sit between graduate programmes and executive leadership initiatives, which means they often receive the least deliberate investment. But they are the people who shape the everyday experience of the largest part of the workforce. They manage teams, influence culture, drive delivery, interpret organisational values for the people around them and become the human face of what the organisation actually stands for.
And they are consistently under-invested in.
Most organisations provide some training when people first become managers and then assume experience will do the rest. The assumption is that good individual contributors will learn leadership on the job. Some do. Many develop habits that are hard to correct later, because nobody invested in shaping them early.
If organisations want stronger leadership pipelines, this is the layer they need to invest in consistently. Today’s mid-level managers are tomorrow’s senior leaders. The quality of investment made in them now directly determines the quality of leadership available five and ten years from now.
“The mix is never fixed. It changes as the business changes. What matters is recognising which phase you are actually in.”