To effectively identify and prioritise opportunities for leveraging generative AI, organisations need to think very clearly about their strategy.  Leadership teams must first establish guiding principles that evaluate the company’s risk tolerance, competitive landscape, technological capabilities, budget constraints, and available skills. Answering critical questions about these factors will help provide a framework for thinking strategically about which generative AI projects to pursue.

Once guiding principles are set, businesses need to gather potential applications across departments and build a comprehensive business case. This requires balancing the interests of three key forces: the enterprising business units, the ROI-focused finance teams, and the more risk-averse IT department. Creating a value map that identifies the biggest opportunities for impact can help build consensus.

Developing a solid business case with input from all stakeholders is crucial. It allows organisations to prioritise generative AI projects that align with their principles, leverage strengths, capitalise on opportunities, and mitigate risks. With buy-in across the organisation, companies can better position themselves in the race to effectively implement transformative generative AI capabilities.

For generative AI to truly thrive, organisations must also build a strong cross-functional ‘AI Team’ with expertise across AI/ML, business domains, data, and IT. Having this diverse team ensures a comprehensive understanding and aligned strategic implementation. Additionally, a robust data infrastructure that can securely store, process, and manage the large data volumes essential for generative AI must be established.

In navigating challenges and risks, ethics must also be a top priority for AI leaders. Adhering to ethical AI standards, ensuring responsible data usage, integrity and maintaining algorithm transparency is critical for fostering trust. Data security, compliance, and regular auditing/updates are also paramount for safeguarding sensitive information that could be exploited. Ultimately, managing change through effective communication, education, and integration of generative AI with existing systems is key to successful adoption. By thoughtfully evaluating opportunities, building a strong foundation, navigating risks ethically and responsibly, and proactively managing change, organisations can position themselves to harness the potential of generative AI capabilities and reduce any risks of falling behind in this fast-moving and fluid evolution.

Paul Wilkins, Associate Director, Russam