How might an internship evolve in to a career in data science?

Andrew Kelly, a senior manager in AI and data at Accenture, shared his journey from an engineering degree to a career in data science and AI. He began as an intern at the company and found his passion for hands-on, applied data science with a clear commercial purpose. This sparked his interest, leading him to complete his master's in engineering and return to Accenture as a graduate, where he continued working in analytics and expanded into business intelligence, data engineering, GenAI, financial services, and banking.

Kelly now focuses on helping banking clients build foundations for AI at scale, including platforms, governance, risk frameworks, and responsible AI processes. He observes that Ireland is "in a promising but unfinished position," particularly in AI adoption. Despite the rapid increase in Irish employees using GenAI tools daily, the impact on organizational transformation remains limited, primarily at an individual level rather than across the company.

While Ireland has the necessary talent, infrastructure, and regulatory framework, Kelly highlights a gap where only about 10% of Irish organizations have reached the 'scaler' status, where AI is fully embedded in core operations. The main challenge lies in strategic clarity, as AI investment needs to be value-led and tied to top-level business outcomes, rather than driven purely by the technology itself.

Kelly emphasizes the importance of shifting from treating AI as a technology initiative to a business reinvention, adopting a process reinvention approach that asks how AI can fundamentally change how work is done and how organizations interact with customers. He notes that skill expectations have evolved, with AI literacy now required across the business, not just among those building the technology.

However, he stresses that the most critical skill is the ability to communicate between technical teams and business decision-makers, translating AI capabilities into business value.

Above all, Kelly finds that genuine interest and a willingness to learn are the most crucial attributes in a career setting. He encourages aspiring professionals not to compare their technical background to others but to embrace curiosity and the continuous learning mindset essential for success in the rapidly evolving field of data science and AI.