Unlocking human potential: Building a responsible AI-ready workforce for the future
Comprehensive workforce strategies, including talent transformation and responsible AI practices, are essential for building an AI-ready culture. Image: Unsplash / Christin Hume
Jasmeet Singh
Executive Vice President, Global Head of Manufacturing and Chair Infosys Public Services and Infosys Automotive GmbH, Infosys- Only 2% of firms are prepared for large-scale AI adoption, highlighting a significant readiness challenge across sectors.
- Comprehensive workforce strategies, including talent transformation and responsible AI practices, are essential for building an AI-ready culture.
- Partnerships among industry, academia, and government are vital to bridge skills gaps and foster sustainable AI innovation.
Two years after the launch of ChatGPT, we are very much in the throes of the AI revolution. As seen with prior technology-fuelled productivity surges, the shift from an experimental technology used in skunkworks to an enterprise-scale solution ultimately results from widespread adoption.
Everyone is, or shortly will be, an AI user. Unlike technologies such as Enterprise Resource Planning, the nature of AI, and specifically generative AI (GenAI), allows its usage to be easily democratized. This enabled ChatGPT’s user base to surpass 100 million within two months of launch. That said, most initial users were individuals rather than corporations. Enterprise adoption is a different challenge.
Enterprise AI readiness research findings
Enterprise AI readiness is a prerequisite for scaling AI. According to an Infosys study, while companies expect productivity gains of up to 40%, only 2% of firms are ready for AI across all five dimensions: strategy, governance, talent, data and technology. This is clearly an issue as, according to the Diffusion of Innovation theory, the tipping point for the adoption of new ideas—at which benefits start to accrue—is between 10% and 25% of adopters. In fact, Siemens considered 50% the threshold for Industry 4.0 adoption among enterprises.
AI adoption challenges occur in many forms. A study done by the collaboration platform Slack reported that employees feel embarrassed to use AI at work, with nearly 50% stating that AI usage would make them appear lazy, incompetent or even like cheaters. Other AI adoption challenges include concerns about hallucination, security, privacy, ethics, bias and lack of tacit knowledge and skills. While strategy, governance, data and technology are measurable, talent and cultural transformation are more intangible and therefore more challenging to quantify and address.
How to build an AI-ready culture
Based on a survey of 1,500 companies and interviews with dozens of business leaders, the following practices have emerged as traits of successful AI adoption:
- Developing a comprehensive AI strategy: Many organizations have adopted a bespoke approach to AI, making it difficult for employees to understand. It is essential to first develop an AI strategy and then communicate it across the workforce. A crucial aspect is helping users appreciate that AI will not replace humans but augment their capabilities and enrich their work. Organizations should therefore apply a human-centred AI discipline.
As AI becomes democratized, organizations need to examine the growing list of associated legal issues. Lawmakers globally are scrambling to create laws responding to legal challenges posed by AI. Since employee actions can expose many legal fault lines, communication and employee education must reflect these concerns.
- Future-proofing the workforce: Among the five dimensions of AI readiness, organizations score highest in talent, with 35% of employees trained and knowledgeable in AI. However, they must not become complacent. AI requires more talent transformation than previous technology waves. Organizations need an AI skill pyramid in which 100% of the workforce is “AI Aware” to fully democratize AI. A smaller group should be “AI Builders” who develop and deploy AI solutions at scale, and an expert cohort should be “AI Masters” who solve complex business challenges using AI.
- AI as the driver for upskilling: A 2023 World Economic Forum paper highlighted multiple job types that will be transformed by AI. With the launch of multimodal capabilities spanning text, speech, image and video, AI can enable upskilling. Online learning platforms integrated with AI can deliver personalized content in the learner’s language and format of choice at a comfortable pace. This helps employees quickly unlearn outdated skills while acquiring new ones for roles that may not yet exist.
- Breaking barriers: The democratized nature of AI presents an unprecedented opportunity for underserved groups to access new opportunities at minimal cost. It could open STEM education to many deserving yet underserved children. It could break language barriers, allowing a farmer in India to exchange tips with a peer in Brazil, each communicating in their own language while AI seamlessly handles translation. AI has immense power but, with power comes responsibility.
- Applying AI responsibly: Organizations must implement responsible AI from the outset. It should not be an afterthought or a bolt-on. The 12 principles of responsible AI include explainability, fairness, security, privacy and regulatory compliance. Being proactive helps AI adoption keep pace with rapidly evolving legal landscapes, while transparency builds trust in the system.
An AI-ready workforce should be savvy with legal dimensions such as AI model licensing, need for use case level approvals, legal issues in training datasets, synthetic data generation and ownership of AI generated content. To address security and ethical challenges, the World Intellectual Property Organization (WIPO) recommends using tools on private clouds and training employees to avoid including confidential information in prompts. For an employee user base to be responsible, it should be actively educated about legal assurances given by AI Product companies about caching of prompts and its usage for training to prevent downstream legal conflicts. Access to AI tools should be limited and controlled if prompts involve copyright, trade secrets or personal data.
We recommend the following strategies to integrate AI into the workforce and unlock human potential:
- Enhance employee capabilities through AI training with diverse, representative data,
- Boost human-AI collaboration ensuring transparency, explainability and accountability,
- Drive business innovation and resilience through responsible AI,
- Foster a culture of AI ethics, trust, continuous monitoring and employee autonomy.
By embracing these strategies, organizations can achieve:
- Human-centred AI design,
- AI fairness and inclusivity,
- Transparency and accountability,
- Continuous learning and improvement.
In doing so, they can fully realize the transformative potential of AI while remaining aligned with responsible principles and human values.
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