Jon Bentley on unlocking future potential: The role of AI in workforce development
Contributing author: Jon Bentley and Shelley Copsey
FYLD is delighted to announce its partnership with Jon Bentley, founder of Zephyr Consulting Ltd (and formerly Partner at IBM Consulting) and his role as advisor to FYLD CEO & Co-Founder Shelley Copsey as FYLD continues its mission to transform field workforce operations in the infrastructure sector.
With a rich background in the Utilities sector, Aerospace & Defense, Oil & Gas, Banking, Healthcare, Government Departments, and Manufacturing, FYLD’s collaboration with Jon will enable its customers to enhance further the value of their investment in a FYLD deployment, and engage with a renowned thought leader on the pressing challenge of workforce development amidst today’s rapidly evolving technological landscape.
While Jon’s professional journey has traversed various sectors, his true passion lies in the energy, environment, and utilities domains—the bedrock of societal progress and well-being. Throughout his career, Jon has dedicated himself to tackling some of the most pressing challenges facing businesses and society. This article dives into perspectives of Jon and Shelley on the role of AI on workforce development with insights on how to navigate some of the latest challenges across US and UK construction and utilities.
The role of AI in the face of current labour market challenges
In today’s rapidly evolving technological landscape, the role of artificial intelligence (AI) in workforce development is becoming increasingly significant. According to the 2021 Workforce Census by the Engineering Construction Industry Training Board (ECITB), the UK’s oil and gas sector is at risk of facing significant workforce shortages if immediate action is not taken to address current skills gaps. The UK Trade Skills Index 2023 underscores the demand for 937,000 fresh recruits in construction and trades within the next decade, with Scotland necessitating 31,000 alone. Furthermore, the aftermath of the Covid-19 pandemic has markedly affected the construction sector in the UK. The looming recession in 2023 further emphasises the need to tackle the skills gap, as outlined in the Construction Skills Network (CSN) report, which anticipates a requirement for 225,000 new workers by 2027.
The UK is not alone in these challenges. A recent statistic from Forbes revealed that about 25% of the U.S. labour force is expected to be 55 years of age or older by 2030, presenting new challenges for public utilities as they lose valuable experience, knowledge, and expertise. E&E News suggests that worker shortages in the US are expected to total more than 1.1 million for occupations across electric, water and wastewater treatment, and “first-line supervisors” for construction and extraction projects.
However, with the advent of advanced AI technologies like Large Language Models (LLMs) and Natural Language Processing (NLPs), there are multiple use cases that can revolutionise how organisations approach skill development, knowledge retention, and task execution.
Transferring knowledge between workforce generations
One of the most critical challenges faced by organisations is the potential loss of knowledge and expertise from experienced workers leaving the workforce. Traditional methods of knowledge transfer, such as documentation, guidance notes, and in-person training, are often insufficient in capturing the tacit knowledge and nuanced insights accumulated over years of experience. However, by leveraging tools such as AI-powered conversational assistants, knowledge sharing platforms, and AI-powered coaching, organisations can ingest and interrogate vast repositories of knowledge, enabling seamless knowledge transfer from experienced workers to newer generations.
These assistants can provide real-time guidance, answer queries, and offer insights based on the collective intelligence of the workforce, ensuring that valuable know-how is retained and accessible to all. Older, more experienced workers play a critical role in training the AI models that bridge this gap which allows conversational AI agents to harness this tactical knowledge.
In the age of AI, the concept of skill shortages is undergoing a transformation, addressing both learning and workforce capacity challenges. AI plays a pivotal role on both fronts. On one hand, AI assistants are revolutionising learning by enabling accelerated skill acquisition at the point of need. By breaking down complex tasks into manageable steps and offering personalised guidance, these intelligent assistants empower workers to learn new skills directly on the job, bypassing traditional training methods and bridging the gap between experienced and novice workers.
On the other hand, AI contributes to increasing workforce productivity by augmenting skills, providing task assistance, optimising workflows, and preemptively addressing potential issues that may disrupt work processes. These features, exemplified by FYLD, enhance productivity at various levels—micro, task level; process or workflow level; and macro, program level. By maximising the productivity of existing workers, AI solutions alleviate workforce capacity constraints, thereby influencing workforce planning, recruitment, training, and management strategies.
In the realm of engineering work, field workers often encounter a unique challenge: the need for specialised knowledge and expertise that may not be required on a regular basis. It’s impractical to train all workers in every aspect of their field, especially when certain arcane equipment or rare failure modes may never be encountered by some. This traditional approach not only consumes valuable resources but also risks the loss of important knowledge over time due to lack of practice. Instead, a more efficient strategy involves providing learning resources at the point of need.
AI assistants play a crucial role here, offering on-demand access to relevant information and guidance precisely when it’s needed. Moreover, there’s potential for AI to extend beyond basic assistance by facilitating connections with remote, highly skilled engineers. These experts can provide immediate support to field workers facing unfamiliar challenges, while also contributing to the ongoing refinement and enhancement of AI capabilities. This symbiotic relationship between AI and human expertise ensures that field workers receive the assistance and knowledge they need precisely when they need it most, ultimately optimising efficiency and effectiveness in engineering work.
The new trajectory of technological advancement
The trajectory of technology development suggests that AI-powered assistants, coupled with intelligent orchestration, will continue to improve over time. In a recent interview with FYLD, Jon Bentley explained, “In most companies, and in most industries, AI deployment so far is in relatively contained and non-mission critical areas. Here again is where FYLD is showing the way: the companies adopting FYLD are doing so right in the frontline where the benefits are greater and more business (and people) critical. This is where AI can have greater impact.”
As AI models become more sophisticated and capable of understanding context and nuance, the effectiveness of AI assistants in augmenting human capabilities will only increase. Organisations that embrace AI-powered workforce development tools stand to benefit from continuous advancements in technology, gaining a competitive edge in an increasingly digitised world.
The role of FYLD’s AI-powered workforce execution platform
In the current landscape, FYLD emerges as a pivotal player in addressing workforce development challenges. By leveraging AI technology, FYLD offers solutions that augment and enhance the skills of workers in real-time. Through continuous learning and feedback loops, FYLD’s AI capabilities enable workers to receive on-the-job assistance, access relevant information, and mitigate risks effectively.
The FYLD App facilitates seamless interaction between humans and AI. We’ve developed a collaborative decision-making environment by offering insights, analysing data, and supporting decision-making processes with our AI models. With our workflow management capabilities, workers receive assistance beyond task execution, ensuring they know the next steps and prioritise tasks effectively. As organisations embrace the future, FYLD stands ready to adapt alongside technological advancements, meeting the evolving needs of the workforce.
Conclusion: AI has the potential to switch ageing workforce and skills scarcity from being constraining issues to drivers of productivity and work quality
The future of workforce development lies in collaboration between AI technology providers and organisations seeking to harness the full potential of their workforce. AI-powered technologies hold immense promise in transforming workforce development practices, from knowledge retention to skill acquisition and task execution. AI is also making significant strides in addressing other workforce and talent-related challenges, such as recruitment, career development, and diversity, equity, and inclusion (DEI) initiatives.
As organisations navigate the complexities of the digital age, embracing AI-driven solutions will be key to unlocking the full potential of the workforce and staying ahead in an ever-evolving landscape.
