AI In The Enterprise: Developing AI Talent
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Ita Petrika-Lindroos
Talent Development Specialist at F-Secure Corporation
Ita runs training and talent development across the full employee lifecycle, with a focus on using AI to improve the employee experience. She is an expert in running training programs via live events and e-learning. Previously, Ita was a Digital Learning Developer at supply chain platform RELEX Solutions, and an HR Development Specialist at Lindström.
Damian Herrick
Global AI/ML Architect, Splunk
Damian manages a team of data scientists and engineers that is building an AI capability centered around governance, risk, and model security. He has 15 years experience as a technology executive, with a focus on cybersecurity use cases for data science, machine learning, and AI. Previously, he was Principal Data Scientist and Team Lead at SAS, and Chief Data Officer at WedPics.
Thomas Bodenski
COO, CDAO at TS Imagine
Thomas is a seasoned data executive with 30 year of experience transforming organizations with technology, data and AI. As COO, Thomas enables rapid commercialization of TS Imagine's real-time trading platform. As CDAO, Thomas leads a department of 50 data scientists and AI engineers, covering everything from data governance to model development. Previously, he was CDAO at management consultancy Element 22, and Chief Knowledge Officer at technology consultancy FOXEYE.
Session Resources
Summary
Developing AI talent in the enterprise is a complex task that involves understanding which AI roles are necessary, how to source and hire the right candidates, and how to upskill and retain existing staff. AI is becoming an integral part of nearly every job function, from data scientists to HR personnel. The discussion highlighted the importance of both technical skills, such as Python programming and AI literacy, and soft skills, such as adaptability and curiosity. When hiring, it's essential to look for candidates who have a strong understanding of how AI can be applied in real-world scenarios and who can articulate the value AI brings to a business. Moreover, creating a culture that encourages continuous learning and development of AI skills can help organizations keep their workforce competitive and engaged.
Key Takeaways:
- AI skills are becoming essential across all job roles, not just technical positions.
- Fusion skills, including AI literacy and process design, are key for adapting to AI-driven changes.
- Hiring should focus on practical experience and attitude towards AI, not just technical qualifications.
- Continuous learning and a culture of curiosity are important to retaining AI talent.
- Clear communication about the role of AI in the company can help alleviate fears of job replacement.
Insights
AI Skills and Roles in the Enterprise
AI skills are no longer confined to data scientists or IT professionals. As AI becomes embedded in various job functions, skills like AI literacy, prompt engineering, and the ability to integrate AI into daily processes are becoming important across the board. According to Thomas Bodenski, "When we recruit, we ask now how has AI helped you do your job." This suggests that having a practical understanding of AI applications is now a differentiator in hiring. Beyond technical skills, soft skills like adaptability and the ability to learn new things are also critical. Ita Petrika-Lindroos emphasizes that AI is not a threat but a tool for enhancing productivity, stating, "It's about learning how to use AI instead of feeling threatened by it."
Hiring and Sourcing AI Talent
Sourcing AI talent involves not just finding individuals with the right technical skills but also those who can articulate the business value of AI. The hiring process at companies like TS Imagine involves rigorous technical challenges to test candidates' real-world problem-solving abilities. Thomas Bodenski notes, "You will be challenged significantly," emphasizing the importance of experience in dealing with AI-related challenges. In the broader market, competition for AI talent is intense, and companies need to build strong employer brands to attract the best candidates. Communication between HR and technical teams is essential to ensure that job postings accurately reflect the skills and experience required.
Upskilling and Retaining AI Talent
To keep AI talent engaged and competitive, continuous learning is essential. This involves not just formal training programs but also creating a culture of curiosity and innovation. Ita Petrika-Lindroos highlights the importance of creating an environment that inspires employees to proactively develop their skills. She says, "We want to build an environment that sparks curiosity." Additionally, providing clear career development paths and opportunities for growth can help retain top talent. Companies must also address any fears employees may have about being replaced by AI, focusing instead on how AI can enhance their roles and make them more effective.
Measuring Success in AI Roles
Measuring the success of AI employees often ties back to business metrics such as productivity gains and cost savings. Thomas Bodenski explains, "At the end of the day, there has to be a monetary impact." This means that even in roles where AI is used to support decision-making, there should be clear, measurable outcomes that demonstrate the value added by AI. For instance, AI can automate routine tasks, allowing employees to focus on more strategic initiatives. The key is to ensure that any AI implementation aligns with the company's broader business goals and delivers tangible benefits.