Why the Adoption of AI Won’t Succeed if We Forget Human Learning

With Rishi Sunak’s recent speech at Tech Week focusing on harnessing the power of AI, the meteoric rise of ChatGPT and Bard, and a constant flow of AI-based solutions emerging just under the surface of public consciousness, businesses are opening their eyes to the opportunities and pitfalls that AI can bring to operational processes. However, fewer businesses are taking the time to consider how this will work in practice, particularly against a background of an ever-present digital skills gap in the UK.

A recent Goldman Sachs report posited that AI could replace the equivalent of 300 million full-time jobs, while campaigners, unions and MPs alike are urging for stricter oversight of workplace AI.

I would argue that the success of AI adoption amongst businesses heavily relies on the ability of the UK workforce to take a fresh approach to digital skills training. This training can give organizations a competitive edge when realizing the full potential of real-world applications and suitability for their business, rather than adopting trendy tech which misdirects the utilization of resources.

The benefits of onboarding AI technology

Machine learning and AI have the potential to significantly boost business growth and streamline processes, if done right. Examples span a range of industries. For one, machine learning has been widely adopted in healthcare, radically improving image-based diagnoses in radiology to genome interpretation. In FMCG, generative AI is helping retailers and e-commerce businesses with speed to shelves through its ability to quickly generate product descriptions, organize data, and supporting branding imagery.

While the practical benefits of using AI are evident, several bigger picture questions, concerns and doubts could be hindering businesses’ progress – and leave them falling short of their commercial objectives. In fact, our recent report found that over two-thirds of UK businesses admit to lacking the necessary digital skillset to achieve their objectives. The correlation between digital skills and growth is undeniable, with 83% of executives acknowledging its impact on their company’s success, leading to 92% reporting the urgent need for skills that are new to the business.

The continuous influx of different AI applications puts HR and L&D teams under pressure to keep up, but throughout the digital age, our emphasis on technology has obscured the human side of the growth equation.

AI today is best understood as a way to augment skills and increase efficiency. Employees must have the right base of knowledge to maximize these contributions, as well as to ensure accuracy and quality. Extracting the greatest value for your people and business

The persistent barriers to skills training, chief among them being cost and the perceived lack of time , must be overcome if businesses are to understand, harness and deploy AI effectively. These five key considerations can help to bridge the skills gap, improve ROI, and increase job satisfaction:

  • Identify the right solutions: L&D strategies must align with business objectives for optimal results. Analyse existing skills gaps across departments, pinpoint immediate issues and prioritise training programs that will address overall performance across the business.
  • Encourage upskilling from the top: While many are realising AI is here to stay, engaging senior leaders and the board on the importance of investing in the human component when implementing AI solutions and processes (in essence, ongoing skills training) is essential to drive commitment and engagement.
  • Motivate employees: Concerns about job loss and dwindling career opportunities understandably follow the emergence of new AI-driven tech. Tackling these fears head on with tailored learning can help individuals to upskill and enhance their professional skillset. It’s worth noting that when development programs align with career aspirations and offer diverse learning options, our research found only 19% of employees struggle to find time for training.
    • Engage with multi-modal learning: Unsurprisingly, a multi-modal approach is more effective than any single training method, with executives at companies investing in multi-modal L&D saying they are significantly more confident in their organisations’ ability to meet business goals (57% vs. 27%). Consider a combination of hard and soft skills training via live learning modules, on-demand training platforms and external specialists to form your business’ training curriculum. Given the concerns that accompany any significant change, we have found that training in growth mindset is particularly effective at unlocking the potential of new technologies while reducing stress.
  • Track and measure impact: Development programs are only as good as the results they deliver, so post-training impact tracking coupled with a constant peer and business feedback loop is essential. Consider setting key performance indicators (KPIs) against cost efficiencies, revenue increases, evaluation of AI skills adoption within and across teams to help inform how your L&D strategy evolves.

The future is upon us

AI presents a challenge and opportunity on a scale that may eclipse the rise of the internet itself. While there is no silver bullet to safe and effective AI adoption, but experience has shown us that to keep pace, we must keep learning.

Digital skills training that addresses current and future skills gaps are critical to future-proof businesses. I would encourage leaders to make a frank assessment of their teams’ readiness to AI adoption into their operational processes and take the necessary steps to bolster existing training and development programs.

[To share your insights with us, please write to sghosh@martechseries.com]
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