Building an AI-ready workforce through strategic multidimensional transformation
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There is no universal solution for AI workforce readiness – success requires a tailored model aligned with each organisation’s unique strategy, culture, and change capacity, writes Sharma Madiraju.
Creating an AI-ready workforce demands a comprehensive multidimensional framework that encompasses change management excellence, innovative human-AI collaboration models, and strategic skills development across all organisational levels. This holistic approach recognises that successful AI transformation extends beyond technology implementation to fundamentally reshape how organisations operate, learn, and evolve.
The emergence of AI is driving a paradigm shift in talent strategy, compelling executives to prepare for a new reality where human-AI collaboration becomes the cornerstone of organisational success. This transformation presents a dual challenge: empowering existing workforce members who possess deep domain knowledge, while simultaneously competing for scarce AI talent in an increasingly competitive market. The leadership imperative is therefore to forge a unified talent strategy that balances targeted external hiring with comprehensive internal capability building, aimed at cultivating a culture of effective human-AI partnership.
Strategic imperatives for organisational leaders
The path forward requires executive commitment to a multidimensional approach that addresses technological, organisational, and human factors simultaneously. Successful AI workforce transformation demands:
- Structured change management: Organisations must implement comprehensive change management practices that build trust, enhance AI literacy, and create shared understanding across all organisational levels. These include transparent communication about the role of AI, addressing employee concerns proactively, and establishing continuous feedback mechanisms. Identifying and implementing the right AI use cases and showcasing the return on investment of those use cases is a key component of the change management.
- Multi-agent collaboration models: As AI systems evolve towards specialised agent architectures, workforce development must prepare employees to collaborate effectively with multiple AI agents that handle different aspects of complex tasks. This requires new skills in orchestrating human-AI teams and understanding how to optimise collaborative workflows. According to “(AI)deation to Impact”, a recent NASSCOM-EY joint study, AI agents increasingly take on routine and rules-based tasks, enabling human workers to concentrate on exceptions, strategic decision making, and complex problem solving. As a result, organisations are redesigning performance models, risk frameworks, and governance structures to ensure shared accountability between humans and AI.
- Skills-based workforce architecture: Organisations must transition from role-based to skills-based approaches, leveraging AI-powered skills mapping and talent intelligence platforms to identify gaps, predict future requirements, and create personalised development pathways. This transformation enables greater workforce agility and alignment with rapidly evolving business needs.
- Demand management: Successfully transforming the workforce for AI integration requires a potent combination of external recruitment and employee upskilling. External recruitment can fill immediate gaps in AI-specific expertise, while in-house upskilling ensures elevated domain skill building and the existing workforce adapts to evolving AI technologies. Upskilling is also cost-effective and helps enhance the retention of in-house domain skills. By aligning hiring strategies with targeted learning and development programs, organisations can create a sustainable talent pipeline that supports long-term AI adoption. This approach fosters a culture of continuous growth, which is essential for thriving in an AI-driven landscape.
Top firms are exploring and embracing different strategic approaches to further gear up their workforce for the AI era.
AI Discovery Week initiative by Canva
In July 2025, Canva set aside a full workweek for its 5,000-plus employees worldwide to focus on AI, during an intensive “AI Discovery Week”. This comprehensive initiative featured internal and external workshops, discussions, and showcases. The initiative also saw collaboration on more than 330 hackathon ideas and over 25,000 hours of learning.
This significant investment was strategically designed to rapidly build AI competencies, enable AI empowerment, and integrate AI into everyday workflows. It helped create an intentional space for employees to learn, experiment, and build together. The initiative also helped encourage employees to experiment with new tools, build confidence in emerging skills, and bring bold ideas to life.
Tailored transformation: A necessity
Ultimately, there is no universal solution for AI workforce readiness – success requires a tailored model aligned with each organisation’s unique strategy, culture, and change capacity. Building an AI-ready workforce represents a critical competitive advantage in today’s AI-driven economy, requiring executive leadership to design bespoke talent models that balance technological capabilities with human strengths.
Tailored talent models are necessary but not sufficient for achieving success. The success of the transformation journey will be determined not by talent models alone, but by empowering people with the skills, confidence, and collaborative frameworks needed to harness the full potential of AI effectively.
Organisations that invest early in multidimensional transformation will gain a sustainable advantage in an AI-augmented world.
Sharma Madiraju is an associate vice president at Infosys.
RELATED TERMS
The term "workforce" or "labour force" refers to the group of people who are either employed or unemployed.
Assessing the business's present and future demands to ensure there is an adequate supply of competent workers and leadership talent is the definition of workforce planning.