By Varghese Cherian – Head of Technology Services, UST
Gartner predicts that Indian IT spend is going to increase by over 11% to around USD 160B in 2025. This change is being driven by investments across six key areas. The areas driving this growth are AI and Gen AI, Data and Analytics, Cyber Security, Modernization, COTS applications, and Infrastructure.
Let us look at each of them in detail to understand where the CIOs will invest, the reason for the investment, and the challenges they could face.
These investments can be looked at in two broad segments, foundational investments and growth-focused investments. The foundational investments will be made in Infrastructure, Data and Analytics, Modernization, and Cyber Security.
Infrastructure traditionally has been behind in terms of investments, but since the advent of cloud computing, the expenditure has become an Operating Expenditure. But as the operating expenses started increasing, enterprises have realized that without proper financial measures, the cost can get out of control. Moreover, cost has started increasing as more services are consumed on the cloud. With the advent of Generative AI and the related challenges of data privacy, enterprises are rethinking investing in their own private data centers to data privacy. This is driving increased investments in infrastructure among the Indian industry. Moving to co-located DCs helps reduce IT spend because the infrastructure can be managed by the vendor instead of needing a large in-house IT team.
Data and Analytics are critical for all enterprises and a fundamental need for implementing AI or Generative AI (GenAI). The challenges have been twofold. Most organizations have grown over time, and therefore their IT sprawl has also and secondly, most organizations have also grown through acquisitions. Over time, this has resulted in multiple data sources of record. This creates an inherent challenge when it comes to leveraging AI within. This results in investments in data lakes and other new-age data repositories that are built to leverage the enterprise data for applying AI. In addition, enterprises are also investing in solutions that provide data visualization capabilities so that the business users themselves can create reports. These investments enable the enterprises to build foundational capabilities to leverage AI. The challenge is that either the in-house IT must be enhanced with these skills or the need for a partner that can help the enterprise create a data strategy for their long-term AI needs and build and support the systems that align with the strategy.
Modernization helps reduce the technology debt in enterprises. As the organization grows, over time, the technical debt also increases. It is seen in stagnant home-grown applications, multiple applications with replicated functionalities, or multiple sources of data. If enterprises have to leverage AI and generate value, they also need to modernize several relevant areas. All these modernizations require investments that they need to put in today to leverage AI tomorrow. The technical debt will never be cleared completely, but it is important to keep it at manageable levels, since old technologies also make the organization vulnerable.
The last area is Cyber Security. Since the four walls of the enterprises were redrawn during Covid, cyber has attracted more than its fair share of investments. As enterprises have realized the need to protect themselves either from outside or from within, they have rushed to invest in new cybersecurity tools. The investments are across tools, SOCs, and in manpower. With the rise of sovereign attacks and malware attacks, enterprises are forced to keep up or suffer breaches and incidents that could be costly. Enterprises must upgrade their SOCs and man these SOCs with the right experts. This is increasingly becoming a challenge, driving most enterprises to consider 3rd party partners to provide these services, to reduce the risk.
The second segment investments are focused on growth. The two growth-focused investments considered are COTS applications and AI.
COTS applications are seeing a renewed interest from enterprises. Unlike the past, when the COTS applications were customized, the current crop of COTS applications is primarily SaaS based and therefore standardized. This helps ensure a best-fit solution for their needs. The SaaS solutions enable enterprises to focus on what. Moreover, even if there are specific customization requirements, there is a method to do this without touching the core product. The only challenge is the integration needs, which increase when you have multiple solutions working together.
The second focus area is around AI and Generative AI. Enterprises understand the need for foundation elements as a critical need for them to leverage AI. They can start moving from proof of concepts into solutions that leverage AI to create value for the organization. There will always be challenges around hallucination and wrongful attribution. But as enterprises either customize LLMs for their contexts or use RAG techniques to tune the LLMs for their data, they will reduce. The other major challenge is with the ethical aspects of AI; to ensure the right guardrails, whether around data and its privacy or around abuse. The other challenge is around the skills needed to leverage AI. Enterprises should build skills in-house while leveraging partners as well. Building a good AI strategy will also be a critical element for their future.
The Indian industries are investing in IT to create value for themselves. But in this tariff environment where clarity itself is a challenge, it remains to be seen whether there will be continued investments in IT or whether the investments will see a trough in the next couple of quarters.