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Culture Is Key to Thriving with Generative AI
Culture Is Key to Thriving with Generative AI

November 23, 2023

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Generative AI (Gen AI) has unlocked new transformational possibilities for business. At this point of disruption, companies have a clear choice: seize the moment to pivot strategically or watch from the sidelines as competitors surge ahead. But what is required to drive Gen AI success? A key element that warrants more attention is organizational culture.

While culture has always been a cornerstone of competitive advantage, Gen AI is accelerating the need for a digital culture. Multiple studies have confirmed that when digital transformations stumble, it’s often less about the technology and more about change management and people-related issues, especially those associated with user adoption. The organization’s culture, demonstrated by accepted behaviors, can act as a barrier to realizing the full potential of Gen AI. A recent Deloitte AI survey highlighted that high-performing organizations are more than 55% more inclined to invest in change management compared with their lower-performing counterparts.

For a successful Gen AI adoption, cultivating a digital culture is crucial. These “3 Ds” can support a cultural change: domain, design and disciplines.

Diving Deeper into the 3 Ds

Domain, design and disciplines are not stand-alone focus areas but interwoven elements. Each amplifies the other, ensuring businesses not only adopt Gen AI but also embed it in their culture.

Domain. At the heart of every successful organization is its depth of domain knowledge — a blend of industry expertise and contextual business understanding that propels performance results and enhances business value. With the advent of Gen AI models, new ways of tapping into a company’s latent data potential at scale have emerged. This shift is evident, with organizations increasingly adopting large language models, fine-tuned on their data, to create a competitive edge. A recent survey further supports this trend, revealing that nearly 40 % of organizations are actively contemplating creating enterprise-specific language models.

Domain and industry knowledge isn’t just vital for successful Gen AI initiatives; it’s an essential element to undertake daily operations and processes. Domain expertise is critical to data and model selection, fine-tuning, prompt engineering, risk management and outcome assurance. In essence, domain knowledge is what unlocks the potential of Gen AI to deliver real business outcomes. 

Design. Over the last decade, design thinking has supported the development of new business strategies, reshaped the customer and user experience, and boosted the progress toward innovation. Co-creation workshops that leverage design practices and cross-disciplinary teams generally achieve faster and better outcomes. Further, co-creation and design approaches can support the ideation, design and development of Gen AI strategies and plans.

This approach not only facilitates the generation of new ideas but also tests the ideas to discern the pragmatic ones from the hypothetical. Design can be a vehicle to reimagine business to harness Gen AI’s capabilities, including data synthesis, human augmentation, insight generation, and automation and scalability. The copilot strategy, with Gen AI augmenting human roles, calls for adopting new design-enabled approaches. This is supported by Deloitte’s research findings, which indicate that organizations are taking decisive steps to establish a robust human-machine collaboration strategy. In fact, 43% have appointed leaders to facilitate more effective partnerships between employees and intelligent machines.

Disciplines. While organizational disciplines shape a company’s culture, they can inadvertently constrain Gen AI’s potential. This can happen when companies become too procedure-compliant, risk-averse and reliant on traditional approaches. To harness the power of Gen AI, businesses must cultivate new disciplines — methodologies, practices and ways of working.

Implementing dynamic, iterative test-and-learn approaches will support the implementation of Gen AI. Agile practices, which have become industry best practices, embody these approaches. For instance, visual development allows teams to create wire frames, iterative sprints that break down complexity into manageable chunks, and cross-disciplinary approaches that encourage collaboration across business users, developers, designers and stakeholders. Additionally, the development of minimum viable products and rapid course corrections enable flexibility.

Cultivating a Holistic Culture for Gen AI Success

As companies strive to embrace Gen AI, assessing and reshaping the organization’s culture will be an important element of success. It’s not just about adopting new technologies; it’s about creating a culture that acts as a catalyst for change rather than a constraint. Considering and addressing the three areas of domain, design and disciplines will support this cultural change. A culture based on domain expertise, design approaches and digital disciplines will help realize the potential of Gen AI. The investments made today in nurturing such a culture will yield exponential returns in the years to come, positioning companies at the forefront of the Gen AI revolution.

Authored by Adrian McKnight, Chief Digital Officer of WNS, a NYSE-listed leading Business Process Management (BPM) company

 

 

 

 

 

 


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