Responsible Artificial Intelligence Adoption in Business

Ellie Fitzpatrick, Head of Data Strategy & Enablement Advisory at BearingPoint Ireland, explores responsible AI adoption, the importance of AI and data literacy, and the role of regulation and governance in fostering innovation. Discover key elements of building an effective AI and data strategy and the essential skills needed for an AI-driven future.

Responsible AI Adoption

Adopting responsible AI is essential in today's world. The vast amounts of data, increasingly volatile geopolitical conditions, and remarkable levels of innovation are all influencing factors.  Organisations must adopt a balanced approach that includes robust governance frameworks, continuous monitoring, and stakeholder engagement to mitigate risks and build trust. By focusing on responsible AI practices, we leverage the technology's benefits while minimising potential harms and avoiding negative reputational impact.  

AI and Data Literacy

AI is now integrated into so many aspects of life, from healthcare to finance to household items! However, data and AI literacy is a critical skill that hasn’t been comprehensively adopted into our education systems.  Despite AI's integration into various aspects of life, there is still a significant gap in AI and data literacy. 

To effectively navigate the complexities of the digital age, it is crucial to educate and equip individuals with the understanding and confidence to use AI and evaluate outputs. From a societal perspective, we see the impact of misinformation on decision-making and behaviours, sometimes with negative outcomes. There is also a fundamental requirement to ensure that the use of data and AI does not exacerbate existing inequalities. From a commercial perspective, there are significant challenges in ensuring that individuals are not disadvantaged in the workforce or as consumers of services powered by emerging technologies. 

It’s also important we avoid creating resistance to the adoption of AI and new technologies, as this could hinder innovation and progress. By addressing these issues, we can promote a more informed, equitable, and forward-thinking society. 

Promoting AI and Data Literacy

Many people are aware of AI's presence in their daily lives, but a deeper understanding of how it works and its implications is often lacking. Without sufficient literacy, we risk widening the digital divide and creating a society that is unprepared for the demands of a data and AI-driven economy.  The inclusion of AI literacy in the EU AI Act highlights the crucial role of individuals in shaping a world where AI can achieve its full potential for responsible innovation and enablement. 

Companies need to invest in education and training programs that equip individuals with the skills needed to navigate and thrive in this new landscape. 

Regulation and Governance

Regulation and governance are key enablers of innovation, especially with emerging technologies. By providing guardrails and parameters, they encourage action.  

For instance, the rapid advancement of generative AI has led to exaggerated claims, legitimate concerns, and nervousness. However, regulation and governance can create a level playing field, fostering confidence to innovate and harness the benefits of these remarkable developments. Productivity enhancements and potentially transformative innovations should be on the agenda for everyone across sectors and industries.  Regulation is usually aligned to the level of risk and is not a blunt instrument; for example, the EU AI Act is risk-based, meaning it is targeted and proportionate. It also gives special consideration to the needs of SMEs and start-ups.   That said, while the positive impact on innovation and ensuring trusted outcomes that enhance a company's brand is significant, organisations still need support in navigating regulations effectively.   

Companies face the challenge of navigating politically influenced regulatory shifts, which can be particularly difficult for those operating on a global scale. But focusing on implementing robust internal governance to implement the more stringent regulatory frameworks will ensure that companies are future-proofed.  

A positive step here in Ireland is the recent announcement by the Irish Government approving the creation of a distributed model for implementing the EU AI Act, with the designation of eight public bodies responsible for AI regulation in their respective sectors. This approach makes compliance more accessible and ensures a balance between innovation and responsible AI deployment. 

Fundamentally, governance and compliance should result in building trust and delivering positive outcomes from Data and AI use. The impact of breaching consumer trust on brand and reputation is damaging for companies but is avoidable with a robust and strategic approach. 

Building an Effective AI and Data Strategy

To build an effective AI and data strategy, companies should start by clearly defining their business objectives and identifying where value can be achieved. Developing an effective strategy requires a holistic view of People, Process, and Technology, with executive-level support. Effective communication and change management are fundamental to an organisation's Data and AI journey.

Getting into the practicalities, organisations must first understand their current maturity by conducting a thorough assessment of their data assets, infrastructure, and people capabilities. This may reveal the need for investment in scalable data platforms, operating model developments and upskilling programmes. 

Collaboration with external partners and staying abreast of industry trends are also key to staying competitive in the rapidly evolving Data and AI landscape. 

A gap or a mistake I often see is that companies think of the Data and AI Strategy as being in the domain of the Technology Teams. But developing an effective Strategy, requires a holistic view of People, Process and Technology. Data and Technology Teams have a key role in influencing and shaping the Strategy, but it must be a wider activity with executive level support.

Ellie Fitzpatrick

Skills and Expertise for an AI-Driven Future

To prepare for an AI-driven future, companies should seek a diverse set of skills and expertise. While data and AI-specific skills are crucial, it is equally important to build expertise in modern data governance and AI ethics. Additionally, companies should look for individuals with strong analytical skills, domain knowledge, and the ability to translate technical insights into business strategies. The so-called ‘softer skills’ such as creativity, critical thinking, and effective communication are essential to foster innovation and collaboration within Data and AI teams. Diversity in teams is essential for fostering innovation and collaboration within Data and AI teams and is is evidentially proven to be the differentiator in successful innovations. 

About the Author

Ellie Fitzpatrick has over 20 years of experience in data quality management, ensuring data accuracy, consistency, and reliability to support business objectives. Over time, Ellie transitioned into data governance and strategy roles in large, complex organisations, focusing on developing holistic approaches to data management. This experience has been crucial in maturing data management, enhancing data quality, automating data processes, and deriving valuable insights from data.