GenAI will be worth trillions. Here’s a roadmap for harnessing it

The rapid adoption of GenAI by consumers and businesses alike, for tasks ranging from image creation to customer support, has transformed B2B companies’ approach to introducing new features. For example, SAP now integrates GenAI to simplify data access, accelerate query responses, deepen customer insights and streamline repetitive tasks in backend processes. Emphasizing intuitive user interaction with software to empower users, we aim to enhance applications’ learning abilities for better and optimized business outcomes. SAP prioritizes ethical practices to avoid bias and ensure equitable growth.

For organizations to succeed in adopting GenAI, they need two overarching building blocks. The establishment of a steering committee at CEO level is imperative, ensuring AI integration is aligned with corporate objectives, receives requisite resources and fosters organizational trust. This helps introduce AI ethical principles and guarantee trustworthy development of the technology.

Secondly, given the dynamic and still-unfolding trajectory of AI, it is paramount for enterprises to foster a culture that thrives on perpetual innovation, with a customer-centric focus; one that emphasizes adaptability, future-proofing talent and promoting ecosystem collaboration. Together, these foundational pillars fortify the seamless integration of AI and position businesses at the vanguard of this transformation.

For AI to be a genuine game-changer, top-down direction is essential. Alphabet CEO Sundar Pichai famously compared the impact of AI to “fire or electricity”, indicating its strategic significance. This centralized decision-making ensures that AI’s transformative capabilities align seamlessly with the company’s vision.

Organizations such as Starbucks, JPMorgan, LEGO and Walmart have created their own AI steering committees at their most senior levels. These cross-functional programs build capabilities and tackle challenges in diverse areas, such as AI use cases and investments, workforce upskilling, partnerships, and legal risks.

The AI maverick team

A dedicated team is crucial. Put at the forefront of AI innovation; this team engages in frequent dialogues with executives and business users. Such teams serve as a crucial bridge, translating the expansive potential of AI into tangible and impactful business solutions.

AI frameworks

AI’s transformative power, which includes increased business efficiencies and breakthroughs across sectors from health to addressing natural disasters, also comes with inherent challenges like biases, unexpected outputs and “hallucinations”. Having robust frameworks in place will provide a roadmap, guiding companies through the complex landscape of GenAI implementation and promote trust. In the banking sector, JP Morgan has established a specialized entity known as Model Risk Governance, whose primary role is to evaluate the risks associated with every implementation of machine learning and artificial intelligence. This rigorous assessment ensures that the deployment of these advanced technologies does not expose the firm and their customers to undue risks.

Governance

The potential of GenAI is counterbalanced by inherent risks, underscoring the need for robust governance. Establishing clear governance ensures that, while GenAI propels companies forward, it does so without compromising ethical and social norms. This is why SAP established an AI ethics steering committee and binding Global AI Ethics Policy years ago covering AI deployment, ensuring proper transparency of features shipped, strong data privacy, understanding of potential bias and harms which must be mitigated, and holding true to their stated commitment to human rights. Current policy initiatives being led by governments and supra-national organizations, include the US AI executive order, EU AI Act and G7 guiding principles and code of conduct, as well as the World Economic Forum’s AI Governance Alliance, NIST’s AI Risk Management Framework and the UN AI Advisory interim report.

Given the nascent stage of GenAI, the onus lies on organizations to go on the offensive with a culture of perpetual innovation to harness its full potential. As witnessed with industry leaders like Microsoft, Amazon, Adobe and Tesla, a forward-thinking approach is paramount.

Going bimodal

Embracing a bimodal approach, pairing predictable, stable and scalable processes with exploration and agility, is essential in the realm of GenAI. Nike embodies bimodal prowess, advancing through incremental improvements of core products and breakthrough innovations in technology and design. They maintain a dual focus on enhancing proven staples and exploring disruptive market trends, ensuring a dynamic balance between sustaining performance and pioneering growth.

Customer-driven obsession

Pioneering a customer-centric approach in the field of GenAI can amplify its impact. The true value of AI in business comes from knowing how to apply AI to solve specific business problems and by putting continuous improvement in place to optimize business outcomes. Here are some examples of customer value-driven GenAI use cases from a recently published SAP white paper:

Collaboration for an AI ecosystem

Hackathons serve as incubators for GenAI innovation, sparking fresh AI ideas to bolster a culture of continuous learning and innovation. To navigate these uncharted territories, organizations must embody a culture of perpetual innovation, as showcased by industry stalwarts. The future of GenAI isn’t just about algorithmic advancements, but more critically about how organizations innovate to deliver real-world impact. It’s about pioneering creativity and innovation by unlocking new dimensions previously deemed unattainable.

The reskilling paradigm

In the dynamic world of GenAI, ensuring talent readiness is pivotal. Companies need to continue making strategic strides in reskilling and upskilling their workforce to remain innovative. Indeed, one of the most important skills for the 21st century will be knowing how to interact with GenAI to optimize outcomes, often called “prompt engineering”. For instance, Adobe has been proactive, offering tailored AI-centric training modules, ensuring its teams are primed for the evolving technological landscape. Wipro recently announced that employees who acquire expertise in generative AI skills, which the company provided at different levels of expertise, will be able to earn a premium salary.