AI is projected to increase labour productivity by up to 40% and profoundly reform the nature of work.
In the past few years, the industry has witnessed tremendous growth in the adoption of artificial intelligence. Still evolving, artificial intelligence is hailed to be the driving force behind the Industrial Revolution 4.0. Undoubtedly, technology has become an imperative part of an organizational set-up. As the technology is accepted amongst the C-suite entrepreneurs, an alteration in the workplace landscape has become evident. The decisions have become technology-driven, whereas the operations have become technology-integrated. A report by Russell Reynolds Associates states that AI is projected to increase labour productivity by up to 40%, and profoundly reform the nature of work. Current estimates show AI creating 2.3 million jobs, eliminating 1.8 million jobs and producing insights that will assist one in five workers.
But as the opportunity promised by technology is mountainous, the challenges associated with its implementation become ambiguous. Current estimates show that the current worldwide population of AI engineers and scientists somewhere between 22,000 and 300,000.
Though organizations are deploying the existing workforce to reap the maximum benefits of this technology, the dearth of AI-talent and the AI-driven business leadership remain the most consequential challenges thwarting the growth of AI in organizations. Undoubtedly, the leaders have recognized these challenges explicitly, but approaching the challenges requires innovative solutions. In this article, we will observe the key points outlined by Russell Reynolds Associated that will aid the organizations in addressing these challenges.
Career Trends and Pathways in AI-leadership
A key strategy that will help address the challenge of dearth in technology is by analyzing the trends and pathways creating hype in the industry.
Current Company’s Industry
The majority of senior AI leaders (35%) currently work within the tech sector, whereas 23% of pure-play AI providers partner with other firms. Additionally, 13% of the AI- leaders are working with the Hardware company and 11% of the AI-leaders lead the software companies.
Past Industry and Functional Experience
Another attribute that holds key-value for redefining the AI-leadership is to observe the work experience of the AI-leader. Close to 42%, which is almost half of the industry leaders, have worked in a start-up, whereas 30% of leaders with a non-technical background gained business experience by founding a new venture. Almost 55% and 34% of AI-leadership have gained business intelligence by working in Software and Hardware Company.
Top Areas of Academic Focus
Though the educational background doesn’t qualify for accessing the leadership of an individual, it provides insight into the problem solving and addressing the capability of an AI-leader. Almost 43% of the AI-leader has a computer science background, whereas 21% have studied artificial intelligence in their graduating years.
Any leadership must not be confined within the gender framework. The diverse leadership helps in flourishing the company. But in technology, the gender difference in AI-leadership is sharply observed. On a demographic level, only 8% of the women are currently entitled to AI-leadership roles. Almost 74% of computer science graduates are male, which creates a major threat in a field that relies heavily on diverse data quality. With a gender gap both in education and leadership, the diversity in the organizational framework is thwarted. It has the potential to become the pitfall of the existing technology.
Essential AI Leader Profiles
Every leader has certain attributes and experience that makes them suitable for the AI-leader profile in an organization. For the AI maturity in an organization, it becomes that the existing leader’s profile must fit with the existing leadership and technology team. Here are the top five AI-leadership profiles and their archetypes that drive an organization for a successful outcome.
1. Cutting Edge Expert– This profile is suitable for sophisticated AI companies where a 1% speed increase in algorithms is a competitive advantage. These experts provide the apex of human knowledge on AI, computer science or data science. Being as well-respected professors., they have conducted academic research and are widely published in AI fields and are making their mark by collaborating with businesses.
2. Renaissance Talent: They are suitable for sophisticated companies focusing on deeper integration between technology and business. By encouraging a balanced mix of technical knowledge, business acumen and social expertise, they are start-up founders having good stakeholder and project management skills.
3. AI-Engineer- They are Suitable for companies in the intermediate stage of AI transformation with a solid strategy in place, and provides a robust framework for scalable AI development and implementation.
4. Unconventional Trailblazer- They are suitable for companies which have met roadblocks while implementing AI, and often bring new energy into the AI transformation journey. These trailblazers provide a fresh perspective on AI as they are unfettered by tradition, usually coming from less traditional backgrounds.
5. AI- Ethicist- They are Suitable for all organizations, especially for large-scale enterprises in which AI would have an outsized impact. They balance business and technical expertise with philosophical and sociological perspectives and advises companies on the implication of AI development, taking into account concerns from the government, citizens, employees and society at large.
Creative Solutions for Sourcing AI-Talent
Since we have discussed AI-leadership above, another challenge regaled countless times is recruiting an AI-talent. Here are the top three solutions which will enable organizations to counter the dearth of AI-talent.
1. Considering Joint appointments– Most AI-talent are already engaged in academics. They are either AI-researchers or scientists who are reluctant to leave their teaching roles and shift to a corporate environment. To bolster AI- capabilities organizations must provide these academicians flexible working arrangements, thus allowing them to hold joint positions both in academics and industry.
2. Re-train Mid Career Employees- Instead of relying on an external factor to address the dearth in AI- talent; organizations must also focus in training their existing employees about AI.
3. Encouraging a Start-up Mindset within the organization- To bolster maximum AI-talent, an organization must also structure their organization like a start-up. This will help in establishing maturity and enthusiasm amongst organizations.
While the challenges are an inevitable part of any technology, establishing a strategical approach would help in maintaining the AI-foundation.