“Businesses too often think of digital transformation simply in terms of shifting technology, and fail to embrace the fundamental cultural shift that is required to sustain such a dramatic change,” said Professor Dana Minbaeva of King's College London in an ITPro article.
Putting people and culture and the center is essential for the success of any major organizational change. Getting your team onboard will smooth the process drastically, and the same is true for AI implementation strategies. Getting the most from them requires that you have the right people involved. The landscape of AI strategies requires a blend of specialized roles, including (but not limited to):
- Product managers
- Business/domain experts
- Data engineers
- AI engineers
- AI architects
- Data scientists
Each of these roles plays a crucial part in translating AI capabilities into strategic business value, according to the AI for the Board — Presentation Materials from Gartner®. But AI will be useful and used by those without specific expertise in the area. Enterprises must take a holistic approach to AI adoption across the organization to ensure optimal productivity, encouraging those in perhaps less technological roles to use the tools at their disposal.
The scarcity of AI talent
However, acquiring such talent is a challenge. A 2021 policy paper by the UK government titled ‘Quantifying the UK Data Skills Gap’ estimated that the supply of data scientists from UK universities was unlikely to exceed 10,000 per year, yet there were potentially at least 178,000 data specialist roles to be filled.
So how do you bridge that talent gap?
- Identify essential skills: Begin by delineating the specific skills and expertise needed for your AI initiatives. This includes not only technical abilities but also the capacity to integrate AI into business processes.
- Upskill current team members: Before looking externally, consider the potential within your current workforce. Upskilling existing employees can be a more cost-effective and loyalty-enhancing strategy. This involves assessing the current skill sets of your employees and determining who could be trained to fulfill these emerging roles.
- Develop upskilling programs: Implement comprehensive training programs focusing on AI and data science competencies. Partnerships with educational institutions or online learning platforms can be a part of this initiative.
- Attract external talent: Despite best efforts in upskilling, some roles may require hiring externally. This necessitates offering competitive benefits and creating an attractive work environment that appeals to the scarce AI talent pool. Highlighting opportunities for growth and involvement in cutting-edge projects can make your organization stand out.
AI and the aging workforce
Another dimension to consider is the aging workforce. According to McKinsey, up to 375 million people may need to change jobs or learn new skills by 2030 due to AI and automation. This presents businesses with an invaluable opportunity to invest in employee development to not only bridge the talent gap but also to enhance the adaptability and longevity of their workforce.
Learn more about how to ensure successful use of AI in today’s business landscape.