Technology Must Be Embedded into Every Solution

You’ve had a fascinating career spanning management consultancy, IT, and now leading practices in cutting-edge technologies. Could you share some key moments that shaped your career path?

There have been several pivotal moments in my career. One of the earliest was on August 15, 1994, when the internet became publicly accessible. At that time, the consulting industry was still predominantly analogue, but as digitalisation took off, it fundamentally reshaped how consulting operated and steered my career in a new direction.

Another defining change occurred as the consulting landscape evolved. In the mid-90s, consulting was largely dominated by Ivy League graduates and consultants from top firms. The focus of Indian entrepreneurs then was on building multinational corporations rather than understanding the global synergies that drive modern business. Over time, this perspective shifted, and now consultants work much more closely with clients, often informally, exchanging insights over meals. Today, our role is to add more value and offer unique perspectives, as clients are more informed than ever.

Finally, we’re living through what I consider the golden age of AI, which is transforming business at every level. AI is reshaping how we work and how we approach problem-solving. For anyone entering the field now, it’s an exciting time, as technological advancements will define this era. In today’s business world, technology must be embedded into every solution; it’s no longer enough to provide only paper deliverables.

You lead practices in AI, edge computing, and blockchain. What excites you most about these technologies, and what challenges do companies face in adopting them?

What excites me most about AI, edge computing, and blockchain is their ability to create innovative solutions to complex challenges. The capabilities these technologies offer are often groundbreaking, even for those of us implementing them. The biggest opportunities — and sometimes obstacles — lie in data. While AI and generative AI are buzzwords today, data remains the foundation. As consultants, we know that data-driven decision-making is essential. However, for AI to be impactful, the quality, governance, and strategic use of data are critical. Many clients don’t struggle with understanding AI’s potential; their challenge is managing and leveraging data effectively. If you, as future MBAs, can help clients unlock the full value of their data, you could drive significant value for their business and yourselves.

What are some of the most innovative use cases you’re seeing for data services and AI in businesses today?

Some of the most exciting use cases for data services and AI in business today span a variety of sectors and applications. Key areas include:

Predictive analytics: Widely used across industries to forecast future trends based on historical data, this is crucial in sectors like finance, where it drives smarter investment decisions.

Natural Language Processing (NLP): Powering chatbots, virtual assistants, and customer service automation, NLP is revolutionising customer support by enhancing interactions.

Computer vision: In sectors like retail and manufacturing, computer vision applications are transforming how businesses manage processes, from quality control to security surveillance.

Fraud detection and anti-money laundering: In banking, AI models are helping detect unusual transaction patterns, preventing fraud, and ensuring compliance with regulations.

Personalised marketing: By analysing individual preferences, AI enables brands to tailor their marketing, boosting engagement and conversion rates.

Supply chain optimisation: AI helps improve the efficiency and resilience of supply chains by predicting demand, managing inventory, and mitigating disruptions.

Healthcare diagnostics: AI-driven diagnostics are transforming healthcare by analysing patient data to predict health risks and suggest preventive measures, which is becoming increasingly crucial as well-being takes centre stage in personal and corporate priorities.

In light of the rapid changes we’ve discussed, what long-term technology trends do you believe will have the most transformative impact over the next decade?

Several key technology trends are set to shape the future over the next decade:

Artificial intelligence (AI) and machine learning (ML): AI will continue to evolve, even though some believe it’s already peaked. The next phase will focus on democratising AI — embedding it more widely into everyday processes across industries.

Internet of things (IoT): IoT will play a critical role, particularly in sustainability and manufacturing. Industries with high emissions, such as those using industrial furnaces, will increasingly rely on IoT sensors to monitor emissions and environmental impact. Connected devices will also be essential in developing smart cities and connected vehicles.

5G and beyond: Although 5G is often linked to faster streaming, its real business potential is just beginning to unfold. It will enable real-time data transfer across complex industrial systems, supporting applications like remote operations and autonomous vehicles.

Quantum computing: This field holds immense promise, offering unprecedented processing power for problems that traditional computing cannot solve. As it matures, quantum computing could revolutionise cybersecurity, simulation, and enterprise systems.

Augmented reality (AR) and blockchain: With the rise of generative AI, blockchain will be key in establishing robust governance models and securing data. Its decentralised architecture provides transparency and trust — critical for future digital transactions and AI governance.

Cybersecurity: As digital connectivity grows, cybersecurity will become even more critical. With more devices and sensitive data in circulation, organisations will need to strengthen their defences and invest in comprehensive security protocols.

Biotechnology and synthetic biology: These areas will see rapid growth, particularly at the intersection of technology and biology. Expect significant progress in personalised medicine, genetic engineering, and sustainable bio-based solutions.

Sustainability and ethics: Technology will play a pivotal role in advancing sustainable practices and ensuring ethical standards. Regulatory frameworks will continue to evolve to keep pace with innovation, ensuring technology serves society responsibly.

Not every emerging technology will succeed, but this will be a defining period of innovation and disruption. Governance, ethics, and thoughtful regulation will be essential to ensure these advances contribute positively to society.

What advice would you offer to young professionals considering careers in management consulting, technology, or talent transformation?

For young professionals aspiring to build careers in management consulting, technology, or talent transformation, here’s some key advice:

Cultivate the right attitude: Approach each task and challenge with a “can-do” attitude. Be willing to step out of your comfort zone and learn continuously. Stay open to both successes and failures, as they are essential parts of the learning process.

Develop T-shaped skills: Aim to build a broad base of knowledge, complemented by deep expertise in a particular area — whether it’s technology, industry, or domain-specific skills. Having a strong core skillset is invaluable, especially as you advance to leadership roles where you’ll solve complex problems.

Gain practical experience: While theoretical knowledge is important, real-world experience often reveals insights that can’t be learned in a classroom. Get hands-on exposure through internships, projects, or side gigs, as these experiences will shape your understanding and adaptability in the field.

Network and build relationships: In today’s interconnected business world, collaboration is essential. No company operates in isolation, so building a strong professional network will open doors and provide support throughout your career. Surround yourself with mentors, peers, and industry experts who can guide you and offer diverse perspectives.

Hone your soft skills: Communication, empathy, and active listening are essential. As a consultant, you’ll be expected to listen actively and offer solutions tailored to clients’ needs. Avoid empty rhetoric — focus on substance and listen more than you speak.

Seek mentorship: A good mentor can provide invaluable insights and help you navigate complex challenges, keeping you on track and accelerating your growth. Mentors can prevent you from losing time by offering guidance and sharing lessons from their own journeys.

Be proactive and persistent: Show initiative in all your endeavours, and don’t be discouraged by setbacks. Resilience is crucial in consulting and tech, where the pace is fast and demands are high. Adaptability will also help you stay relevant as technologies and industry needs evolve.

Maintain work-life balance: Burnout is a risk in high-pressure fields like consulting and tech. Prioritise your well-being to sustain your performance over the long term. Find ways to recharge so you can approach work with renewed energy.

Be authentic: Stay true to yourself. Recognise your strengths and areas for improvement, and focus on continuous personal growth. Authenticity builds trust with clients and colleagues, which is essential in any consulting or leadership role.

Commit to lifelong learning: Especially in fields driven by technology, learning never stops. Make it a goal to acquire new knowledge and skills daily. Staying curious and continuously evolving is key to staying competitive and effective.

IBM Consulting emphasises ‘the science of consulting’ and leverages AI in its delivery platform. Could you elaborate on what this means and how it differentiates IBM Consulting from other firms in the industry?

IBM Consulting’s emphasis on “the science of consulting” is about leveraging data-driven insights, automation, and advanced technology to enhance precision and efficiency in consulting engagements. Historically, consulting in India, like many industries, relied heavily on labour arbitrage — offering cost benefits through human resources. However, the focus is now shifting toward asset-based value, where proprietary tools and technological innovations provide a competitive edge. In this context, IBM’s approach is distinctive due to its integration of advanced technologies, particularly AI, to drive efficiency, customisation, and scalability.

At the core of IBM Consulting’s methodology is data. Every decision is informed by data-driven insights, allowing consultants to provide clients with tailored, fact-based solutions. This approach addresses the risk of obsolescence that many companies face by ensuring decisions are grounded in current, relevant information. Furthermore, IBM Consulting’s delivery platform, the IBM Consulting Advantage, embodies this “science.” It acts as a centralised knowledge repository, housing IBM’s best practices, insights, and historical data from over a century of consulting experience. By querying this platform, consultants can rapidly access insights, industry perspectives, and ready-to-use summaries, significantly reducing research time and enhancing productivity.

Additionally, IBM Consulting’s integration within IBM’s larger ecosystem of software, research, and technology groups provides access to robust resources that many competitors lack. Unlike other firms, IBM Consulting operates not only across IBM’s own products but also across a wide range of technologies, supported by a dedicated research and development infrastructure. This comprehensive setup allows IBM to consult at scale and deliver solutions with greater agility, often completing in hours what might take competitors days.

Ultimately, the “science of consulting” at IBM means continuous learning, innovation, and applying AI-driven efficiency to solve client problems faster and more effectively. This approach resonates with clients, especially as they see IBM’s ability to deliver insights and solutions swiftly and reliably, setting IBM Consulting apart in an increasingly competitive industry.

The new IBM–Microsoft Experience Zones offer hands-on access to cloud and generative AI solutions. Can you describe a specific example of how a client might use these zones to explore and address a real-world business challenge?

The IBM-Microsoft Experience Zones provide clients with immersive, hands-on access to advanced cloud and AI technologies, enabling them to explore and address real-world challenges in a collaborative environment. IBM and Microsoft have created these zones to foster innovation by bringing together their unique strengths: IBM’s deep industry knowledge and decades of IP, and Microsoft’s extensive technology ecosystem.

A client example might involve a company seeking to improve its supply chain efficiency. In the Experience Zone, IBM and Microsoft experts could work with the client to prototype a customised solution using Microsoft’s AI and cloud technologies. This would allow the client to see how the technology could address their specific supply chain needs, such as optimising inventory levels or reducing lead times. The zone provides a “sandbox” environment where they can quickly test and validate ideas with real- time support from IBM and Microsoft experts, reducing the usual trial-and-error phases in technology adoption.

Moreover, these zones are designed to help clients overcome common obstacles in digital transformation. For example, many organisations face skills gaps when trying to implement new technologies. IBM addresses this by offering skills development sessions, showing clients how to make the most of Microsoft’s technology suite. This collaborative approach not only enhances the client’s confidence in the solution but also accelerates time-to-value by involving IBM’s and Microsoft’s domain experts to tailor the solution in real-time.
Beyond prototyping and skill-building, the zones also facilitate strategic planning. After clients gain insights into how a technology solution might work for them, they often proceed to work with IBM on a long-term roadmap, using insights gained from the zone to develop a comprehensive digital strategy. This ability to bring a business problem from concept to strategic planning — all in one environment — sets IBM apart in the consulting field.

In essence, these zones are co-innovation spaces where IBM and Microsoft can engage directly with clients, blending cutting- edge technology with deep industry expertise to create solutions that are both practical and transformative.

Let’s say a company implements a generative AI platform to streamline its recruitment process, but it struggles to quantify its impact on hiring efficiency and cost-effectiveness. How can it effectively measure the ROI of this GenAI investment in talent transformation, considering factors like improved candidate quality, reduced time-to-hire, and potential cost savings?

When a company implements a generative AI platform to enhance its recruitment process, assessing the return on investment is essential but can be challenging. This process begins by identifying and quantifying the impact of AI on key performance indicators (KPIs), capturing improvements in both efficiency and effectiveness.

One important factor is time-to-hire, which refers to the reduction in average time taken to complete each recruitment stage, from initial screening to final onboarding. By automating tasks that were previously manual, such as resume scanning and interview scheduling, AI can drastically shorten hiring cycles. This reduction directly translates into cost savings, as quicker hiring cycles mean fewer resources are tied up in recruitment over extended periods.

Another critical measure is cost per hire. By automating repetitive and time-intensive tasks, generative AI reduces the expenses associated with these stages. The company can compare the reduced costs against the initial investment in AI technology and consulting to determine whether the automation leads to significant financial benefits.

The quality of hires is also a valuable metric. Generative AI platforms can offer data-driven assessments that better align candidates with job requirements, resulting in improved performance and retention. By tracking these post-hire performance metrics, companies can assess whether AI-driven hiring translates into fewer turnover costs and higher productivity, as well as reductions in costs associated with replacing poor hires.

Diversity and inclusion are increasingly significant in modern recruitment. Generative AI tools, by design, can minimise unconscious biases in the hiring process, promoting a more inclusive workplace. If the AI platform helps to achieve higher diversity rates, this adds a tangible, strategic value to the company’s recruitment practices, potentially enhancing the company’s culture and brand reputation.

The scalability of the AI platform is another factor to consider. As hiring demands fluctuate, particularly during rapid expansion phases, the AI tool’s ability to handle these changes without significant manual intervention can save time and reduce operational bottlenecks. An effective platform should allow for scaling from small to large hiring volumes smoothly, offering cost savings over manual processes.

Lastly, automating as much of the recruitment process as possible provides the most significant time and cost efficiencies. By setting an objective to automate all recruitment steps aside from the final interview, a company can significantly streamline its operations. Job posting, candidate communications, and response management can be fully automated, reducing the need for human intervention, which otherwise incurs additional costs.

By focusing on these KPIs and benchmarking them against pre-implementation metrics, a company can evaluate whether generative AI aligns with its recruitment objectives and adds both immediate and long-term value. This structured approach provides a clear, data-driven framework for quantifying ROI and understanding the strategic impact of AI in talent acquisition.

How does the collaboration between IBM and NVIDIA specifically address AI challenges?

The collaboration between IBM and NVIDIA combines IBM’s extensive consulting and industry expertise with NVIDIA’s cutting-edge hardware and software solutions, including GPUs and AI enterprise software.

This partnership is designed to streamline AI workflows and optimise model development by leveraging the best of both worlds. IBM provides its deep domain knowledge, industry insights, and expertise in enterprise solutions, while NVIDIA offers the high-performance hardware and software needed to handle complex AI tasks. NVIDIA’s GPUs, for example, provide the necessary computational power to accelerate training and inference, while IBM’s AI-powered platforms and
cloud infrastructure enhance scalability and manageability.

In short, NVIDIA serves as our hardware accelerator, delivering the raw computational power needed to push AI boundaries, while IBM brings its expertise in AI model development, optimisation, and deployment. This synergy ensures that our clients can take full advantage of AI’s potential, from conceptualisation to large-scale implementation.