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Thu, Sep 19

Artificial Intelligence, and most recently GenAI, has been raising quite a stir. Indian-grown GenAI startup Sarvam.ai made headlines by raising one of the largest Series A rounds ever, with $41 million.

Globally, the AI market is expected to grow to a whopping $360 billion by 2027, with GenAI accounting for 33% of it. Indian tech investors have deployed over $700 million in AI and GenAI just in the last year.

Yet, what does all this buzz translate to for the tech services industry? While most companies have a well-defined go-to-market strategy in place, only a few have succeeded in realizing the benefits, and only a few champions have emerged.

So, what have these champion players done differently? There are five things they are doing differently that have helped them scale pilots and realize the benefits:

1. Co-creation of solutions: Shifting from "creating a solution for the client" to "creating a solution with the client" has been a game changer for a few firms, wherein IT players have started working with their clients to co-create solutions right from the PoC stage in a consultative fashion where clients have their own teams involved from the start. This enables a sense of buy-in and ownership from the client from the get-go, encouraging clients to move to production should the pilot see success. For example, a player worked with a Big 4 on how GenAI could help increase effectiveness in a typical audit process flow.

2. Realizing value at PoC stage: Select firms have started realizing value at the Proof of Concept stage itself, instead of just demonstrating potential value. Clients see the ROI and can appreciate that it is not just a concept, therefore have a higher readiness for a large-scale implementation. For example, a player demonstrated and eliminated over 90% manual work for select use cases for their client's video analytics platform at the PoC stage, which led to a full-scale production deployment.

3. Paid PoCs: While initially many players invested in free PoCs with end customers, it is mainly the paid PoCs which have seen higher conversion. Clients take the PoC more seriously when they pay for it and will often engage much earlier on and throughout the process. The industry has realized this as well, with over 80% of PoCs being paid for by clients in recent months.

4. Verticalized/Specialized Platforms: A few players have built customized verticalized platforms, focusing on niche vertical specific cases. This also allows them to act as both a repository of implemented client cases and as an innovation tool to constantly build new use cases, allowing player to rapidly build and scale PoCs.

5. Client education and awareness workshops: Top players have run GenAI education workshops for their clients focused on not only showcasing their solutions, but also highlighting the "art of the possible" beyond commercialized use cases. These workshops have worked best when both business & tech C-suite clients have representation in the room. For example, a top tier tech player has run over 100 workshops with end clients and has seen a significant impact on their sales.

Beyond these imperatives, it's critical to ensure that clients at all levels are adequately educated on the potential of GenAI and that expectations are managed upfront. Furthermore, internal capabilities for IT players, particularly those with a formal setup such as a Center of Excellence (CoE), are essential for the smooth delivery of client projects. Often, having an innovation budget also facilitates rapid idea generation and demonstrates a deep level of commitment to clients.

To summarize, securing client buy-in from day one-whether through co-creation or paid PoCs, demonstrating impact early on, educating clients upfront, and allowing them to experience GenAI solutions-has significantly helped IT industry leaders scale from pilots to production. However, IT players must remember that while focusing on scaling is important, embarking on this journey requires having the right vision, governance, operating model, people, technology, and data in place.

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