Vinoliah Martin - Client Executive, Board Member and PhD Researcher.

In today’s contemporary business landscape, Artificial Intelligence (AI) and now generative AI has emerged as a key priority for leaders across industries. The transformative potential of AI is inspiring leaders to explore its possibilities and harness its capabilities to revolutionise business outcomes, ignite innovation, improve productivity and enhance customer experiences. From predictive analytics to natural language processing, AI is penetrating every facet of business, enabling companies to gain a competitive edge. The true power is unlocked when both AI and generative AI are employed in tandem to democratise the access and utilisation of AI. According to research conducted by PwC, 45% of the anticipated economic gains by 2030 will result from AI-driven product enhancements, spurring consumer demand through increased product variety, personalisation, attractiveness, and affordability over time (https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf).

The extensive and continually growing array of use cases for both AI and generative AI is truly remarkable. These range from streamlining customer self-service processes and enhancing agent performance to accelerating process optimisation, driving product innovation, and boosting employee productivity, to mention to a few. Alongside this, the pervasive fear of missing out (FOMO) on the benefits offered by AI is undeniably real. Leaders do not want to fall behind their competitors, lose their market share, or miss out on the potential growth and innovation that AI can bring. They want to be proactive, agile, and responsive to the changing needs and expectations of their customers, the workforce, and their stakeholders. To effectively harness some of the benefits of AI, certain considerations deserve attention:

Vision and strategy

One of the first challenges leaders often face is to define a clear and compelling vision and strategy for harnessing AI and delivering value to their organisation and stakeholders. Establishing a comprehensive vision for AI implementation requires leaders to delve into the intricacies of their organisation's structure, operations, and overarching goals. It is not merely about adopting the latest technological trends but rather about aligning AI initiatives with the strategic objectives of the organisation. A clear vision serves as the guiding light, providing direction for an organisation's AI journey. It requires leaders to ask fundamental questions for example: How can AI contribute to achieving our long-term goals? How can AI improve the workforce productivity? What innovative opportunities can AI unlock for our customer and stakeholders?

It is important to realise that AI is not a one-size-fits-all solution that can be indiscriminately applied to any problem or opportunity without careful consideration. Developing a robust AI strategy requires a multi-faceted approach. Leaders need to assess the quality and accessibility of their data, and the skill sets present within their workforce. Data is the lifeblood of AI, influencing the effectiveness of applications and the potential for innovation. The success of AI initiatives hinges on the careful curation and management of data, making it imperative for leaders to not only evaluate the current state of their data infrastructure but also strategize for its improvement. This involves addressing issues of data quality, ensuring accessibility, and establishing robust governance frameworks, and conscientiously addressing biases present in historical data used to train AI models.

Culture

Then there is culture, it is imperative that leaders shape a culture that embraces AI and supports its responsible and effective use. This includes fostering a mindset that view AI as a tool to augment human capabilities and not as a threat to job security. In doing so, leaders should instil a mindset of curiosity, creativity, and continuous learning among the workforces.

Having a curious and creative mindset means approaching the world with an inquisitive spirit and readiness to think innovatively. Curiosity drives individuals to explore new ideas, take risks, and view failure as a learning opportunity. This coupled with creativity can then allow individuals to think outside the box, connect disparate ideas and generate unique solutions to problems.

Continuous learning is an integral component of a thriving organisational culture. Beyond formal education, the workforce can leverage continuous learning by identifying their career goals, engaging in online courses, attending workshops, training and seminars, seeking feedback, reading industry publications and embracing a growth mindset.

Some online platforms include:

• LinkedIn Learning: Provides a vast library of video courses on business and technology- https://learning.linkedin.com/
• Udemy: Offers a wide array of courses on various topics, with a focus on practical skills. - https://www.udemy.com/
• Coursera: Offers a diverse range of courses from universities and organisations worldwide. - https://www.coursera.org/
• Microsoft Learn: Offers training on Microsoft products and technologies - https://learn.microsoft.com/en-us/training/
• AWS free tier: Offers hands-on experience of the AWS platform, products, and services. - https://aws.amazon.com/free

Creating a culture of continuous learning also requires leaders to be empathic. Leaders can do this by:

• Recognising and rewarding learning and reinforcing the idea that learning is a valuable and appreciated endeavour within the organisation.
• Ensuring that employees have the necessary resources to pursue continuous learning and offer support in balancing work and learning commitments.
• Create an environment that is conducive to open communication and idea sharing.

Ethics

The final consideration is ethics. Ethical AI and responsible AI is often used interchangeably, but these terms are distinctly different. Ethical AI, is about making morally sound choices and is intricately connected to values and social economics. Responsible AI, adopts a more tactical approach, addressing the manner in which we develop and utilise technology. It places emphasis on the practical aspects, ensuring that AI systems are safe, secure, robust, transparent, diverse, inclusive, and accessible. Together, these efforts can facilitate the creation of AI systems that not only benefit individuals and humanity but also contribute positively to societal well-being.

As AI becomes more deeply ingrained in our daily lives, ethical considerations cannot be overlooked. Leaders need to prioritize ethical and responsible AI to build and maintain trust with stakeholders and customers. Almost every consulting and technology company holds a perspective on ethical and responsible AI.

Mckensey sets the stage for a responsible AI framework, focusing on 10 key guiding principles:

https://www.mckinsey.com/capabilities/quantumblack/how-we-help-clients/generative-ai/responsible-ai-principles

1. Accurate & reliable: When developing AI systems, ensure outputs are trustworthy and dependable.
2. Accountable & transparent: Provide transparency into development and use of AI systems and how decisions are made.
3. Fair & human-centric: Design AI systems with human oversight and diverse perspectives to mitigate risks of unfair discrimination and harmful biases.
4. Safe & ethical: Prioritize the safety of human life, health, property and align AI systems, with ESG principles.
5. Secure & resilient: Mitigate potential cyber threats and vulnerabilities.
6. Interpretable & documented: Design AI systems to be interpretable, allowing humans to understand their operations.
7. Privacy-enhanced & data governed: Pay careful attention to privacy, security, confidentiality, and intellectual property.
8. Vendor & partner selection: Exercise diligence and ongoing oversight when selecting third-party vendors involved in AI system development.
9. Ongoing monitoring: Establish standards for continuous monitoring and evaluation of AI systems to uphold ethical, legal, and social standards.
10. Continuous learning & development: Ensure adaptive training, user education, and regular compliance auditing to remain aligned with ethical, legal, and societal standards.

In conclusion, I believe that realising the benefits of AI necessitates a synergistic alignment of vison, strategy, culture and ethics. When these elements converge, organisations can unlock AI's potential to enhance productivity, foster innovation, and drive significant business value. AI is a powerful and transformative tool that can bring many benefits to humanity; however, a tool can also be used as a way to destruct and destroy, it is therefore imperative that leaders ensure that governance and policies are in place for the responsible use to AI as AI stands as a powerful force for good!