Vijay Guntur on How Human-AI Collaboration Can Drive Enterprise Success in 2026 and Beyond

As enterprises face a more complex AI landscape, one reality remains evident: human-AI collaboration is essential for meaningful transformation. This is further reinforced by the findings of the 2025 State of Enterprise Technology survey, which underscores that driving AI at scale is no longer just about choosing the right model – it’s about preparing the people, processes, and infrastructure to support it.

To explore this further, we spoke with HCLTech CTO and Head of Ecosystems Vijay Guntur, who likewise claims that the biggest AI opportunities in 2025 were often missed – not because of technological limitations, but because organizations underestimated the importance of aligning their people with AI-driven transformation.

In this conversation, Vijay shares actionable insights on how companies can move beyond “AI laundry lists” and achieve tangible business impact. He emphasizes the value of human-centric change management, workforce upskilling, and fostering cultures of curiosity, empathy, and adaptability.

He also offers a forward-looking perspective on the challenges and opportunities enterprises will face in 2026 and beyond.

From sustainable AI deployment and responsible AI frameworks to the rise of centralized AI platforms and the human-AI collaboration of the future, Vijay provides guidance for business leaders, CTOs, and professionals looking to thrive in an AI-driven world.

Year-end reflection

You’ve said many enterprises missed the biggest AI opportunities this year in 2025 -not because of technology, but because of change management and not aligning their people with the use of AI. Can you elaborate more on this?

Guntur: In my experience, one of the biggest mistakes organizations can make during their digital transformation are not technical. It is underestimating the importance of change management.

Many companies concentrate on implementing new AI tools. But fail to properly prepare and align their people for the changes these technologies bring. When organizations set out to do something transformative, they must think about employees’ aspirations and motivations.

Successful AI adoption requires clear communication, education, and support, so people feel involved in the journey rather than threatened by it.

When organizations do not invest enough in understanding and addressing employees’ aspirations, motivations, and concerns, and skip the step of clear communication, resistance can grow, and transformation progress stalls or fragments the company culture.

Another issue is treating AI purely as a technical rollout, without building the right skills – both technical and human – across the organization.

HCLTech puts a lot of emphasis on internal education and technical certifications, where we have already trained 100,000+ of our employees to use  AI technologies. It is also important to foster essential human qualities like communication and empathy. These combined elements are crucial for ensuring teams feel empowered, engaged and AI-ready.

Ultimately, aligning the workforce with AI transformation means

• making people central to the process,

• investing in their development, and

• fostering a culture of openness and continuous learning.

When organizations get this right, the technology follows – and so does real business impact.

The “AI laundry lists” (companies have laundry lists of what they want AI to do) have become common in boardrooms. What’s your advice for leaders trying to move from a checklist approach to achieving real, measurable business impact with AI?

Guntur: We often see organizations come to the table with extensive laundry lists. And sometimes with over 200 AI ideas – that they’d like to pursue.

My advice for leaders is to distill these long lists down. Instead, focus on a set of 10 to 20 high-impact and feasible uses that are tightly focused on their core business objectives.

Prioritize these initiatives based on both business value and time to value. Then you can build proof of value from those real-world uses, deliver measurable benefits and scale the AI solution across the teams and relevant organizational units.

This approach not only ensures resources are invested wisely. But also accelerates time to value and builds confidence in further AI adoption.

Success comes from treating AI as a strategic business driver, not just a technology checklist. Focus on what will move the needle for your organization, measure results rigorously, and scale what works.

Creating the right balance

How can leaders create the right balance between technological innovation and humans – especially as AI changes the nature of work itself?

Guntur: AI adoption is happening faster than any technology we have seen before. Yet the learning curve is steep, because it’s new for everyone. We’re all trying to understand how to harness AI responsibly and effectively.

The balance between innovation and human centricity is key. The future workforce won’t be defined by technologies replacing humans – it will be shaped by humans empowered by technology. AI isn’t about only doing more with less, it’s about expanding access, amplifying potential and creating opportunities at scale.

The next-generation workforce will thrive at the intersection of human creativity and machine intelligence. And leaders must ensure that this workforce is prepared.

The most valuable skill won’t be technical alone – it will be the ability to learn, unlearn and relearn, to stay curious and being adaptable as technology keeps evolving. And that’s where training, upskilling and constant learning will be essential for leaders to implement AI into their organizations.

Those who embrace that mindset – who see reskilling and upskilling as a lifelong journey – will be the real leaders of this new era of progress.

As AI reshapes workflows, what new human skills will define the most successful digital-first professionals over the next few years?

Guntur: First, I think it’s important to clarify that engineering is not all technical. Engineering also includes skills to communicate and listen.

As AI continues to transform workflows, learning abilities including curiosity, listening and empathy will become more critical to work effectively alongside intelligent systems.

It can help teams collaborate, adapt to change, and ensure that technology is used to amplify human potential rather than replace it.

Another emerging skill set, where human curiosity and adaptability is an integral asset, is “prompt engineering” – the ability to craft sophisticated inputs that get the best results from AI systems.

As digital interfaces become more conversational and natural language-driven, knowing how to interact with AI effectively will be a significant differentiator.

At HCLTech, we’re investing in both technical and human skills development. Because we see that the future of work belongs to those who can blend technology with uniquely human abilities. Continuous learning, adaptability, and emotional intelligence will define the most successful professionals in the AI era.

Leadership

How can leaders cultivate human strengths in teams increasingly working alongside intelligent systems?

Guntur:  As AI becomes more integrated into the workplace, it is essential for leaders to cultivate human strengths that drive collaboration and innovation – like active listening, understanding others’ perspectives, and a willingness to learn and explore new ideas.

At HCLTech, we believe this starts by fostering an environment of integrity, which is one of our core values. Our approach to change management includes training, certification, and hands-on demonstrations, along with regular education sessions designed to introduce new technologies and help teams adjust to the evolving needs of our clients. Our senior leadership and board members have been oriented as well.

These initiatives support teamwork, adaptability, and ensure that technology is used to enhance and advance employees’ potential.

Q. What role should the C-suite leadership team play together in ensuring that AI transformation strengthens company culture rather than fragmenting it?

Guntur: People development is at the heart of our people strategy at HCLTech and should be for every organization to help accelerate the transformation of learning, skills and workforce readiness in an AI-driven world. That is where the partnership between a CTO and CHRO or a CEO is essential.

The relationship between CTO and other C-Suite executives is to build a culture where people’s skills are viewed not as a threat but a tool for growth, encouraging constant learning, career development and adaptability for the future of technology.

Responsible AI

With the increasing use of AI in decision-making, how can leaders build and maintain trust and transparency – especially around AI?

Guntur: As AI evolves and rapidly scales, it is important that sustainable innovation is underpinned by responsibility and trust. This means implementing guardrails to enable responsible AI at every stage of AI development. It is essential that responsible AI is a core aspect and the center of a company’s operations to ensure that AI technologies are deployed ethically, sustainably and for the benefit of all.

At HCLTech, we have already established governance frameworks to enable responsible and ethical use of the technology. These comprehensive Responsible AI (RAI) frameworks align with global standards such as NIST, the EU AI Act, ISO and similar laws ensuring transparency, accountability and protection against fraud, bias and misuse.

The road to 2026: Emerging challenges and opportunities

As we head into 2026, AI inference costs and energy usage will become pressing issues. How should leaders prepare for the growing sustainability challenge in AI?

Guntur: As we move into 2026, inference costs and energy usage are going to become some of the biggest issues facing AI adoption. The complexity and scale of AI models mean unit costs and power of inferencing is going to drop as technology evolves. Leaders need to be proactive and thoughtful in how they approach this challenge.

One of the biggest lessons we’ve seen at HCLTech is the importance of prioritizing. By identifying and focusing on the most critical AI needs, companies can direct their resources to the right use cases, helping them scale efficiently, and deliver return on investment.

From an operational standpoint, we believe AI Factories or centralized, repeatable platforms for developing and deploying AI, will become pervasive. HCLTech has already implemented these platforms that make it easier to see return on investments from AI.

We are also seeing a trend where certain AI workloads move away from public cloud and back to private or hybrid environments which may better manage power and sustainability.

It is also crucial for business, technology, and operations leaders to work closely together and keep value front and center throughout the AI lifecycle. By taking these steps, organizations can keep innovating with AI while also keeping an eye on sustainability and the bottom line.

Which industries or sectors do you believe will get most creative with AI in 2026, and why?

Guntur: In 2026, the most creative use of AI will come from industries that can move quickly – especially those that are less regulated. We’re already seeing rapid adoption of AI in across sectors in customer experience and marketing automation.

What’s especially exciting is the rise of vertical-specific applications, such as AI-powered drug discovery in healthcare, where organizations can “fail fast” and accelerate breakthroughs.

Physical AI and robotics are also expanding beyond manufacturing, where it is already common in warehouse and other relevant sector settings. Robots are now moving into sectors like energy, utilities, data centers and worker safety, among others. Industries that are agile and open to experimentation will lead in AI innovation.

Future perspective for the next five years

How do you envision AI will transform enterprise operations and innovation models over the next five years?

Guntur: Over the next five years, AI will fundamentally reshape enterprise operations and the way organizations innovate.

We are seeing AI agents and co-pilots become increasingly common, making interactions – whether with customers or within the enterprise – much more natural and intuitive.

As people grow more familiar and comfortable using agents in their everyday lives – like virtual assistants in banking, hospitality, or even at home – they will also become more open to adopting these innovations in the workplace. This growing comfort with conversational interfaces and digital agents will accelerate the integration of AI into business processes.

In terms of operations, AI-driven automation is streamlining everything from HR and hiring to marketing and customer experience. As more agentic AI systems mature, shifting from just being a response system but becoming capable of reasoning and personalizing responses, enterprises will need to invest in ongoing monitoring, tuning, and validation to ensure reliability and trust.

On the innovation front, I see the rise of AI Factories, or centralized platforms for developing and deploying models at scale and accelerating how quickly organizations can bring new solutions to market. Physical AI and robotics will expand into new sectors such as energy, utilities, data centers, and even hospitality and will unlock new ways of working and delivering value.

In time, AI will become the foundation for operational excellence and continuous innovation. Organizations that combine technical and human skills, foster a culture of experimentation, and keep people at the center of their transformation journey will thrive.

How do you see the relationship evolving between AI and humans in the coming years?

Guntur: When thinking about the future of AI, it is essential to remember that technology is always intertwined with human interaction. As AI becomes more integrated into our daily lives and workplaces, the relationship between humans and AI will continue to evolve and it will be collaborative.

As AI takes on more routine and repetitive tasks, the distinctly human skills – like learning ability, curiosity, and empathy – will become even more important. These qualities help people adapt, innovate, and build meaningful connections in an increasingly digital world.

At the same time, new technical skills will rise in importance, such as prompt engineering and the ability to effectively use and guide AI systems.

Future success for any enterprise will depend on blending human strengths with technical expertise, ensuring that technology amplifies human potential rather than overshadowing it.

Top 5 takeaways for 2026 and beyond

This interview gives five takeaways for 2026 and beyond

Technology isn’t enough

Technology alone cannot do it all. Workforce alignment, upskilling, and innovative culture are critical to realizing AI’s full potential.

Focus on high-impact initiatives

Leaders should move beyond “AI laundry lists” and prioritize projects that deliver measurable business outcomes.

Human-centric skills matter

Curiosity, empathy, adaptability, and growth mindset are essential for the AI-driven workforce.

Responsible and sustainable AI

Leaders and tech teams should address ethical considerations, governance, and energy efficiency to build trust and long-term value.

Future-ready enterprise

Centralized AI platforms, agentic AI, and emerging technologies like quantum computing will redefine operations and human-AI collaboration over the next five years.