Adopting Generative AI: A Strategic Guide

Know Your Tactical Advantage
Generative AI has made this tech accessible for everyone. But while this democratization has increased productivity and reduced costs, it also means that these same tools and advantages are available to competitors as well.

To address this “downside” of democratization, CEOs and business leaders need to identify their unique use cases, and also choose the path of least resistance, at least initially. Look for use cases that are unique, low-risk, easy to implement, and which offer the greatest productivity boost across the organization. They can be from any point across the value chain – for example, integrating generative AI into customer engagement, augmenting R&D and summarizing documents, producing content etc.

Plan Your Investment
Considering the “newness” of gen AI, CEOs need to carefully assess the timing and scale of their investment. They must prepare and prime their business for it – invest in R&D, hire a partner that offers in-depth AI consulting and AI services, get active buy-in from all key stakeholders, and leverage institutional knowledge. Start small by piloting generative AI in a small, focused business area and figuring out what works and when/what to iterate. Due to the inherent propensity for errors in generative AI, it’s best to opt for use cases that can accommodate a certain degree of variability in their outputs compared to use cases that require extreme precision. Depending on the specifics of use cases, leaders also need to make strategic choices about whether to fine-tune existing language models (through prompt tuning and prefix learning), or train a custom model which although is a relatively extensive investment, yields deeper and more long-term impact.

Prepare and Enable Your Knowledge Workers
Knowledge workers, across diverse domains, play a critical role in driving innovation and growth within organizations. Under the guidance of a trusted AI consulting company, CEOs need to work with their leadership team and HR to redefine knowledge workers’ roles and responsibilities and adjust operating models accordingly. One smart approach is to break down a certain job/role into different sub-tasks, and identify which of them are human-intensive, which can be automated, augmented, and which are the new “novel” tasks. This is the new mix around which companies should redesign their workforce to extract maximum value, make informed decisions, and accelerate their digital transformation journey.

Protect Your Business
While experimentation should always be encouraged, on a strategic level, it’s important to put up guardrails and be aware of the risks that ad-hoc, awkward adoption of generative AI can bring. CEOs need to have policies and procedures in place, covering responsible use of AI, clearly-defined data ownership, and process to review content before it’s released. In addition, leaders also need to ensure protection of company and client proprietary data, and mechanisms to regularly update security protocols and policies.