Summary Bullets:
• HCLTech is taking a wise approach to building customer confidence in its GenAI services by offering outcomes-based pricing models.
• Tying compensation to performance, which can include KPIs and ROIs, is a logical next step.
GenAI is considered the most disruptive technology in the market today. Momentum is strong, with the market opportunity expected to grow from $2.8 billion in 2023 to $75.7 billion in 2028, a CAGR of 94%, as projected by GlobalData’s latest forecast. Enterprises across a range of industries are eager to harness the benefits of GenAI in a wide variety of use cases. The technology can be used to support customer service and marketing initiatives, improve operational efficiency, enhance security and fraud prevention measures, modernize applications, and much more.
However, challenges abound. Many projects don’t move past the experimentation phase to full deployment. And despite enthusiasm for GenAI initiatives, which often comes from lines of business teams, projects often take longer than expected and require more resources than originally anticipated. The need for integration with existing systems, a lack of a strong foundational data management structure, and a shortage of internal expertise can hinder project momentum. Furthermore, the complexities around emerging trends such as adoption of RAG, customizations of guardrails, incorporation of on-premises deployments, interest in agentic workflows, and security concerns create numerous challenges.
Enterprises are often reluctant to engage with third parties for help with GenAI deployments. They note a lack of confidence in their abilities, claiming that consultancies lack expertise in the new technology. Instead, they prefer to build internal skills and avoid paying steep prices for consultants that don’t deliver. Furthermore, enterprises also note that high turnover at large IT services providers (ITSPs) inhibit continuity and delay projects.
To counter these concerns, HCLTech is taking a wise approach to building customer confidence in its GenAI services. In addition to the usual strategies of sharing customer testimonials (marquee customers come from a range of industries, including banking and financial services, insurance, retail, automotive, travel, hospitality, healthcare, and life sciences); opening AI labs and delivery centers; collecting numerous hyperscale cloud provider certifications; and building out teams of local talent in Asia, the US, and Europe (as well as collaborating with educational institutes to develop talent), HCLTech is enticing customers by offering outcomes-based pricing. The ITSP is committing to clients that they will only charge for their services once projects are in production. The company is being forward-looking with the strategy and proactively offering the pricing model to customers and tying outcomes to timelines. The engagements are often AI-led deals that also include application modernization and data transformation components.
The new pricing structure complements HCLTech’s AI portfolio, with focuses on moving customers from experimentation to production. HCLTech recommends that enterprises think beyond machine learning models, and focus on modernizing data assets, evaluating strategies for communicating insights, and creating a foundation that paves the way for scaling AI deployments in the future. HCLTech’s portfolio consists of AI and GenAI Engineering (semiconductor and hardware engineering), AI Force (service transformation for IT & businesses process efficiency), AI Foundry (embeds AI across workstreams), and AI Labs (ideation to minimum viable product). Looking ahead, the company plans to expand its already strong partner ecosystem and convert offerings to industry-specific solutions.
HCLTech is wise to demonstrate to customers that it is committed to seeing projects come to fruition. Over and over again, customers note the challenges of implementing GenAI, but express hesitation when it comes to working with third party vendors. Additionally, the market is not committed to any one type of vendor for professional services – enterprises are open to working with hyperscale cloud providers, telecom services providers, software vendors, small consultancies, and large ITSPs. Furthermore, with a renewed focus on FinOps and the re-evaluation of cloud strategies that sees the hyperscale cloud providers offering pricing incentives to woo customers to their AI platforms, HCLTech’s decision to roll out pricing models that set it apart from the competition is a smart move. Tying compensation to performance, which can include KPIs and ROIs, is a logical next step.