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December 04, 2023

Gen AI: turning headwinds into tailwinds

By taking these three actions with generative AI, businesses can turn a time of uncertainty into immense opportunity.

If it’s certainty you’re looking for, you’ve come to the wrong economy.

The recession that’s been “looming” the last several quarters still hasn’t arrived. But it hasn’t stopped looming either, and businesses remain in a defensive crouch—scrutinizing budgets, keeping discretionary spending tight and focusing on investments that promise a short-term return on value.

There’s just one challenge: the tectonic shift in the business environment created by generative AI.

There will be clear winners and losers in this new era defined by generative AI. Early adoption is key. In our recent survey of senior business and technology executives in the US and UK, in fact, 99% are enthusiastic about this new technology, with 61% predicting a complete transformation of their business.

It is time for companies to dispense with the “blue sky” thinking and resulting paralysis-by-analysis. If you’re going to win, you must act.

Three key actions

By “act,” I mean making three types of practical, measured, enabling investments that position you to capitalize on generative AI with maximum optionality: data, training and large language models (LLMs).

Investing in AI without addressing data quality challenges is akin to constructing a house on an unstable foundation. AI systems heavily rely on high-quality data to generate accurate insights and help you make informed decisions. Businesses that neglect data quality compromise the very essence of AI's potential. They risk undermining the trust in AI systems, eroding confidence among stakeholders and jeopardizing desired outcomes.

Next: skilling and training. A defining marvel of gen AI is that it can take instructions and deliver outputs in natural language, but that doesn’t eliminate the need for worker training. Far from it. To maximize gains and minimize risk, companies need workers grounded in basic AI principles—primarily model development and prompt engineering.

Cognizant, for example, recently launched its “Synapse” initiative, which seeks to train one million global workers in cutting-edge technology skills, including these foundational principles, by 2026.

The final core investment: the LLMs that power generative AI applications. Here, the key is getting to value quickly, creating competitive advantage. There are generally three approaches to building LLMs:

  1. License an existing model and fine-tune it. Work with a global systems integrator to layer in the integrator’s sub-industry specific data and tailored models. Then, fine-tune it with your company’s proprietary data to securely create unique, competitive advantage that will set you apart from the competition.

    We’re doing this right now in partnership with Google Cloud, modifying Google’s PaLM LLM to serve a host of clients in the payer sector of the healthcare industry. We’re harnessing all the power of PaLM’s original training data, enhanced with our own industry data, as well as proprietary business data from each client, to build applications that are both powerful and uniquely tailored to transforming administrative processes in areas such as appeals and grievances, and member and patient engagement for healthcare clients.

  2. Build your own LLM from scratch. While this is potentially the most powerful and flexible option, it also requires the most time, money, skills and data. Unless you’re a major tech company, along the lines of a Microsoft or Google, this approach will tie up resources that could be better used in your core business delivering value to customers.

  3. Use an open, public model like GPT-4. While this is the fastest way to stand-up an LLM, it fails to leverage proprietary data to provide organizations a competitive advantage. It also requires data privacy and security due diligence.

Turn uncertainty into opportunity

Generative AI’s arrival, in short, makes this a fitting moment to stop bracing for economic turbulence, and start turning uncertainty into opportunity.

Commit to these core investments now, and you may one day look back on this uncertain macroeconomic moment as an inflection point: the start of huge, even radical growth for your business.

To learn more, visit the Generative AI section of our website or contact us.

Surya Gummadi

Executive VP and President, Cognizant Americas

Surya Gummadi

Surya Gummadi is President of Cognizant Americas, responsible for the strategic direction and operational performance of Cognizant’s business in the US, Latin America and Canada. Additionally, he is responsible for the global large deals team.

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