Simply deploying AI and expecting it to transform your workforce will result in misplaced solutions and organisational fatigue, says Oliver Shaw CEO of Orgvue
Artificial intelligence is rewriting the rules of engagement for workforce transformation. While investment remains high and organisations are placing big bets on the technology, the over-simplistic view that AI will replace jobs in their entirety leaves many businesses exposed to lost talent and compromised productivity.
Our research from last year shows that while 82% of organisations had invested in AI and 33% planned to increase their investment, 50% admitted they were unclear how the technology would impact their business.
The rush to deploy AI is largely driven by a fear of missing out, as companies jostle to be seen as innovative and competitive. But there are many pitfalls to this approach, particularly when investments are made without a full understanding of how to integrate the technology into the workforce effectively.
How will AI fit in?
AI’s role in an organisation extends beyond automation. When deployed well, it can redefine job roles, streamline processes, and enhance decision making. To capture AI’s full potential, organisations should first undertake a thorough mapping and re-engineering of their business processes to accommodate the new technology.
By identifying tasks that are suited to automation and matching specific technologies that can fulfil them, businesses can avoid misplaced deployments that underperform or that are error prone. To bring this point to life, our research indicated that while 69% of organisations were confident AI would be embedded in core business operations by the end of 2025, 39% said they lacked the organisational expertise to achieve this.
Furthermore, employee scepticism (36%) and a lack of regulation (33%) also stand in the way of effective AI adoption. There’s also the issue of technologies over-promising business benefits or misrepresenting what they can achieve as solutions to particular challenges. And it’s becoming clear to many that a data-driven approach is essential to distinguish genuine and appropriate AI capabilities from conventional tools dressed up as AI.
Getting strategic AI deployment right
The cornerstone of successful AI deployment lies in strategic planning and data-driven decision making. Organisations are better off adopting a 360-degree view that takes into account not just the immediate benefits of AI but also the long-term impact on workforce dynamics and organisational structure.
Organisations that excel in workforce transformation are those that continuously review and adjust their business strategy based on data and insights. By doing so, they can anticipate challenges, mitigate risks and unlock new opportunities for growth and innovation.
“Fear-driven decision-making will eventually stifle innovation”
AI washing: The fear of missing out
The practice of overstating the capabilities of AI technologies, known as “AI washing”, is usually driven by an organisation’s fear of falling behind its competitors. Investment encouraged by AI washing can lead to the adoption of inadequate or misplaced solutions, which will ultimately hold back workforce transformation. Businesses caught in this cycle are likely to see a low return on their investment, wasted resources, and loss of opportunities for innovation.
Fear-driven decision-making fosters a culture of reactivity rather than strategic proactivity. Such an approach will eventually stifle innovation and lead to organisational fatigue, as employees struggle to keep up with the constant changes brought about by poorly understood technology deployments.
To avoid this, businesses should prioritise organisational design to fully understand how to apply AI technologies appropriately. A simple process such as the following can help:
- Analyse – Gather, synthesise and examine data on your current workforce and organisational structure. Look at tasks and activities in detail to find automation hotspots based on the work.
- Design – Model different organisational scenarios and test designs.
- Plan – Apply data insights to your workforce plan to align with business goals, identifying gaps between workforce demand and supply.
- Monitor – Continuously track organisational performance, repeat steps 1 to 3, and make adjustments as needed.
Understand your workforce
A good starting point for any organisation looking to deploy AI at scale is to understand workforce demand and supply in detail, then use this insight to see where AI can close gaps and automate low-value work.
Organisations need to recognise that AI won’t magically transform their workforce and make their business better by default. Like all technologies, AI is just an enabler, not a panacea.
Workforce transformation needs careful planning, a clear view of organisational skills, and a strategy that puts people first. And that’s no different for AI. Once businesses acknowledge this fact, they’ll have a much better chance of delivering the value that AI promises.
Oliver Shaw, CEO of Orgvue
Further reading
This story was first published in Business 4.0