Moving forward, it will be difficult for IT teams to “go it alone” when it comes to coordinating all the elements that need to come together to build a robust GenAI strategy. With the right partners, however, anything is possible.
“Innovate or die,” Peter Drucker’s 1985 exhortation on the importance of constant reinvention, was great business advice for the last 40 or so years. But things have gotten a little more complicated now, as the large-scale roll-out of generative artificial intelligence (GenAI) has introduced the need for a multidisciplinary approach to innovation. Today, it is not enough just to innovate within one’s own vertical; to truly exploit the power of GenAI to transform workflows and drive competitive advantage, CIOs need to look outside their own organizations to get the scale, domain expertise, and speed required to develop fully integrated solutions.
Building an effective GenAI strategy is about much more than launching a point solution or siloed group of tools that only work for one part of the business. The real power of the technology is its ability to draw on disparate data sets and connect workflows. Achieving that seamlessness between business functions and across geographies requires a new approach by CIOs. In fact, there are five key areas CIOs need to consider when developing an enterprise GenAI strategy, all of which become much more achievable with the right partnerships in place.
Developing a data-led strategy
The first, and most critical step in the process is accessing, integrating, and curating the underlying data that will be used to train and power AI models. This is a challenge for many CIOs. According to an EXL Enterprise AI study, 74% of C-level leaders say data silos have been a barrier to enterprise-wide AI implementation. In banking and financial services applications, for example, GenAI solutions are being developed to analyze customer data, market data, economic trends, and more to help support highly personalized insights and guidance.
Likely, they will need to exploit all the latest tools provided by cloud and data partner ecosystems to manage, govern, scale, analyze, and secure their data before they can deliver these types of solutions. Furthermore, CIOs will need to partner with large language model (LLM) developers to fine-tune GenAI algorithms based on the business use and the ease with which these models can be integrated with their existing data layer fabric.
Modernizing the legacy tech stack
As part of this data integration effort, CIOs will also need to take a hard look at their existing tech stacks to evaluate whether they are up to the task of fully cloud-based, seamless data transfer. Many organizations still rely on legacy systems that can be challenging to maintain, upgrade, or integrate with newer technologies. CIOs must devise strategies for modernizing legacy systems while ensuring a smooth transition and minimizing disruptions to business operations. Partner ecosystems of cloud service providers (CSPs), cloud data, platform providers, software vendors, and systems integrators play an important role in these migration and modernization efforts by providing support for things like agile framework development, data and talent transformation, and long-term planning. Likewise, the tech giants developing LLMs and cloud platforms will find significant benefits by partnering with domain experts who have the know-how to integrate their offerings into highly specialized use cases.
Making the business case
CIOs will also need to partner internally across their own organizations to align their technology efforts with core business goals. Gone are the days when cool new technologies could be developed just for the sake of it. GenAI has now reached a level of maturity where investments made are being judged against the results generated. To maximize the value of these investments, it will be critical for CIOs to take a page from digital native companies like Netflix, Uber, and Airbnb by linking technology development directly to customer experience and working together seamlessly between teams to prioritize technologies that have the biggest impacts.
Security and data privacy
The introduction of GenAI into enterprise workflows, and the related data needed to power it, amplifies the need for CIOs to implement robust security measures, develop incident response plans, and stay vigilant against evolving cyber threats to protect sensitive information and maintain business continuity. This can be particularly challenging in heavily regulated industries such as healthcare, insurance, and finance. By collaborating with a CSP, CIOs can gain access to technical and industry knowledge they need to navigate the complexity of bringing their technology stacks fully into compliance. This expertise may be impractical or impossible for them to access otherwise because the talent and investments that CSPs make to protect their public and private cloud infrastructure is unparalleled.
Additionally, by tapping the combined expertise of LLMs, CSPs, and domain experts, CIOs will be in a better position to start using GenAI tools to spot anomalies in their data, creating early warning systems for detecting fraud and cyber security risks.
Budgets to build new innovations
It’s always a challenge to find the budget to build new innovations and platforms when the primary focus of the CIO is to keep the business running. Self-funding mechanisms, although feasible, are often not suited for large-scale transformation efforts and faster time-to-market needs. Most of the CSPs are willing to invest in the CIO’s modernization efforts that are coupled with data center exits or application migration efforts. CIOs must leverage the partner funding programs, specifically offered by CSPs, to fuel their journey to the cloud with an eye on the business case. CIOs can therefore focus on building new industry-focused platforms and micro-services, harnessing the power of the platform economy, by leveraging the partner resources for their digital transformation.
Putting the pieces together
The GenAI revolution holds to potential to revolutionize business by connecting the dots between once disparate data sets to improve workflows, deliver more personalized customer experiences, and streamline operations. But it’s going to be tough for any one tech team to go it alone when it comes to wrangling all the components that need to come together to build a bulletproof GenAI strategy. With the right partners, however, anything is possible.
At EXL, we’re seeing the results of powerful partnerships every day as we collaborate with our clients, CSPs, platform providers, and other specialized technology providers to deliver fully integrated GenAI solutions that are transforming the way businesses operate.
Learn more about how EXL can put generative AI to work for your business here.
About the authors:
Vishal Chhibbar is chief growth & strategy officer and Sumit Baluja is global head of strategic partnerships and advisor relations at EXL, a leading data-and AI-led services, digital operations, and solutions company.
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