Hina Patel, Managing Director and Data, AI & Gen AI lead for Accenture, Africa.

In today's rapidly evolving business landscape, the integration of artificial intelligence (AI) into corporate strategy has become a critical leadership imperative. As AI starts to impact all kinds of organisations, it's clear that the skills required at the executive level are shifting toward a more technical orientation. It is noticeable that the world's most successful listed companies are now largely led by individuals with a strong background in engineering or programming, exemplifying the increasing need for technical acumen to navigate and mobilise AI effectively.

The adoption of AI is not just about staying competitive - it's about redefining how organisations operate, deliver value, lead and manage talent and sustain growth. Here are five key imperatives for leadership in the age of Generative AI:

1. Create real value

The primary objective of AI adoption should be to create value for customers and stakeholders. Technology just for technology’s sake is a mistake and instead, leaders must focus on how AI can drive business value. This involves identifying areas where AI can make a real difference by identifying value and impactful business cases, optimise operations, enhance customer experiences, and open new revenue streams. For example, predictive analytics can improve supply chain efficiency, while tailored customer recommendation services and offerings can enhance user satisfaction.

To achieve this, executives need to align AI initiatives with their business strategies. It requires cultivating an understanding of both the technology that is available as well as the evolving business landscape that creates certain needs or gaps within organisations. AI investments need to be impactful, and value driven.

2. Have a strong digital core

A strong digital core within an organisation is fundamental to leveraging AI effectively. This includes a robust data infrastructure, advanced analytics capabilities and cybersecurity measures. An organisation’s digital core is the backbone for all its operations and ensures that those operations can be managed and scaled more effectively.

Building this foundation might involve addressing data readiness and governance, upgrading legacy systems, adopting cloud solutions, and ensuring that best practice data governance practices are in place. Fostering a culture that values data-driven decision-making is crucial in today’s world. When an organisation’s digital core is strong, it can harness AI to drive insights, productivity, and other efficiencies, and deliver innovation at scale.

3. Harness talent and new ways of working

Embracing new ways of working, that go beyond traditional workflows into transformative business processes, is essential in the age of exponential AI. This includes fostering a culture of innovation and agility, where employees are encouraged to think creatively and adapt to modern technologies. Leaders must prioritise retaining top talent and investing in their development. This involves creating opportunities for employees to acquire new skills and adapt to new roles using data insights and AI tools.

Leaders must also prioritise diversity and inclusion within their teams, as varied perspectives can drive innovation and lead to more effective AI solutions.

Re-skilling programmes should focus on both technical and strategic aspects of AI. For instance, training programmes can cover data science, machine learning, and AI ethics. Additionally, fostering a collaborative environment where employees can experiment with AI tools and technologies will drive innovation from within.

Executives should also recognise the importance of attracting new talent with AI expertise. Building partnerships with educational institutions and participating in tech communities can help in this regard. By nurturing a talented and adaptable workforce, organisations can stay ahead in the AI and business ace.

4. Pursue only responsible AI

As AI becomes more integral to business operations, ethical considerations must take centre stage. Responsible AI involves addressing biases, ensuring compliance, and maintaining transparency and accountability through ethical governance. Leaders must champion ethical AI practices to build trust and safeguard their organisation’s reputation.

This includes implementing robust governance frameworks that oversee AI deployments and ensuring that AI systems are fair and unbiased. For example, regular audits of AI algorithms can help identify and mitigate biases, and transparency in AI decision-making processes can foster trust among stakeholders.

Leaders should also stay informed about evolving AI regulations and standards. By proactively addressing ethical and compliance issues, organisations can avoid potential pitfalls and position themselves as responsible AI leaders.

5. Continuously embrace change and collaboration

The AI landscape is dynamic and constantly evolving. To thrive today, organisations must cultivate a culture of continuous learning and adaptation. This means being open to current ideas, experimenting with emerging technologies, and iterating on AI strategies.

Leaders play a critical role in fostering this culture. They must encourage a mindset of exploration and experimentation. For instance, adopting a “three Es” approach – explore, experiment, execute – themselves in the first place, can help them foster an organisational culture that makes it possible to innovate effectively. By bringing in training programmes for their teams, exploring new AI applications, experimenting with pilot projects, and scaling successful initiatives, leaders can drive continuous improvement within their organisations – ensuring that their organisations can stay relevant and excellent even in volatile market conditions.

Leaders who embrace change will stay informed about AI advancements and industry trends. This might involve attending conferences, engaging with AI communities, and investing in ongoing education so that they can continue to make informed decisions and guide their organisations through change.

Being open to change also means being open to collaboration. Effective leaders must cultivate a collaborative environment both internally and externally. Internally, this means breaking down siloes and fostering cross-functional teams that can innovate more holistically. Externally, forming strategic partnerships can enhance technological capabilities and innovation potential. These partnerships might include collaborations with AI research institutions, technology providers and industry peers. By leveraging the strengths and expertise of various partners, companies can accelerate their AI initiatives and achieve greater impact.

Conclusion

Leading in the era of exponential data and AI requires a strategic, informed, and ethical approach. While playbooks are being developed, organisations are still learning. One of the best approaches for leaders is to get involved and experiment themselves as they discover the vast possibilities that AI, Gen AI and data science can open up for their organisations. C-suite executives who are open to learning will be far more adept at navigating the complexities of AI and drive their organisations forward than those who are risk-averse, suspicious, and resistant to change. The opportunities to use AI are immense in modern responsive organisations.

As AI continues to redefine the business landscape, the imperatives for leadership extend beyond traditional management skills to include a deeper understanding of AI and its value, a commitment to ethical practices, a proactive approach to talent management, adapting ways of working and ecosystem collaboration. Leaders who can navigate this complex terrain will position their organisations for success in an AI-driven future, fostering environments where innovation thrives and where AI enhances both operational efficiency and strategic growth.

AI-informed leadership has never been more critical.