Most enterprises are accelerating AI adoption, but many are struggling to demonstrate measurable business value. Harsha Anand Almad, global head – People & Change Consulting at Wipro, argues that the next phase of AI transformation will be defined less by technology deployment and more by redesigning work, reshaping talent models and enabling people and intelligent systems to collaborate effectively. In an interview with Sudhir Chowdhary, she explains why workforce strategy must evolve alongside AI. Excerpts:
AI is the buzzword among enterprises today; do you think AI deployment is moving in the right direction?
While the enthusiasm around AI continues to gain momentum; most AI investments are being driven by urgency and a fear of missing out (FOMO) to competition, rather than a clear strategy. Most enterprises fast track AI deployment and realise later that the business outcomes are not aligned with their initial expectations.
Many organisations measure AI activity, such as the number of pilots launched or tools deployed, but struggle to connect those investments to impact. Our recent research with HFS found that nearly nine out of ten organisations are investing in AI faster than they can prove business value, while only 21% are fully confident that their AI investments are delivering measurable outcomes.
Closing this proof gap requires organisations to move beyond technology deployment and focus on redesigning work, workflows, accountability structures, and workforce models. AI creates the most value when it is embedded into how work gets done rather than layered onto existing processes.
How is AI changing workforce strategy for enterprises across industries?
We believe that the future workforce will consist of people and intelligent systems working together toward shared outcomes. The benefits of AI cannot be achieved through technology uplift alone. It demands deliberate shifts in contextual workflows, capabilities, operating models, culture, and the very architecture of work.
As AI becomes an execution layer, workforce strategy needs to evolve to design ecosystems for humans and AI to collaborate efficiently. Smart organisations are rebuilding the talent architecture, redesigning how work flows between people and intelligent systems, how decisions are made, and where accountability sits.
AI has reignited concerns about workforce reduction across the technology industry. Are those concerns justified?
Every technology shift has changed how work is performed, but AI is different because it is affecting work at every level of the organisation simultaneously. However, jobs will not be disrupted by AI, rather, people who leverage AI more impactfully stand to benefit immensely. Additionally, the success for enterprises will be determined by how they reskill and repurpose their workforce to do new jobs that require AI skills.
Organisations need to prepare people for new categories of work that require higher levels of judgment, creativity, domain expertise, and collaboration with intelligent systems. Certain skills that were earlier defined as critical are also evolving. While technical literacy remains important, skills such as critical thinking and problem solving are becoming increasingly valuable.
How will AI change the traditional talent model for organisations?
Traditionally, organisations have built capability through the apprenticeship model. Early career professionals learned by performing tasks, managers learned through oversight, and leaders learned through years of accumulated decision-making. As AI automates portions of that learning journey, organisations need to rethink how expertise is built, how institutional knowledge is transferred, and how future leaders are developed.
This means moving beyond traditional reskilling programmes and redesigning the entire learning model. Employees need earlier exposure to decision-making, structured coaching, and real-world business contexts. At the same time, the expectations of managers are changing. Their role is no longer limited to reviewing output or allocating work. They need to help teams interpret AI-generated insights, challenge assumptions, apply business context, and make better decisions. The enterprises that enable a future where humans and machines grow smarter together will turn AI ambition into a durable enterprise advantage.
What has changed in Wipro’s approach to workforce and talent transformation?
Wipro has been continuously investing in AI skilling at scale across our global workforce. We are focused on creating role and persona-based learning pathways for AI. There has also been a shift in the skills we prioritise. Technical expertise remains important, but increasingly we are looking for a combination of AI literacy, domain knowledge, business understanding, problem solving, and decision making.
The most significant change is that workforce transformation is now directly linked to business outcomes. We are ensuring that people can continuously adapt, apply new skills in real client environments, and work effectively alongside intelligent systems to deliver measurable value. This also reflects a broader shift from a traditional hire-and-train model towards a continuous learning model, supported by talent pipelines, university partnerships, and earlier exposure to emerging technologies and business problems.