In November 2022, forecasters from the Metaculus group stated that they believed there was a 50% chance that Artificial General Intelligence (AGI) would be achieved, evaluated, and announced to the public by the year 2040. However, due to recent break throughs in generative AI technology, such as OpenAI’s video generator SORA, Metaculus’s timeframe for achieving AGI has become even shorter.
A study conducted by Katja Grace that surveyed 352 AI experts, cross referenced with two other surveys conducted in 2018 and 2019, showed that 50% of experts believe that AGI will be realised by 2060. 90% of experts predicted that AGI will be achieved within the next 100 years. However, as to the exact date, whether it be in 20 years, 30, 100 or more, experts are highly divided.
This is due to the highly speculative nature of such predictions. Although in the last four or five years there have been exponential advancements made in generative AI that have led many to believe that we are getting ever closer to realising more human-like AGI, the nature of this technology and its development does not allow for one to make a precise prediction (Grace, 2024). Predicting the pace of any technological developments is challenging, there are numerous factors to be considered:
The development of algorithms and computing power.
The level of investment and global interest in AI research.
Ethical and regulatory considerations that may slow down and shape the path of development.
Scientific breakthroughs in understanding consciousness and human intelligence better.
It is important to approach any predictions with caution and remain aware of the multitude of factors at play, however, we will share our 20-year estimates regarding the future of Enterprise Resource Planning in Field Services Management and AI.
By 2045, Work Management and field service management are likely to be significantly transformed by advancements in robotics, generative AI, self-driving cars, drones, and self-diagnosing and self-repairing systems.
The future of work management is poised for a shift toward autonomous operations, integrating technologies like self-driving vehicles, drones, and robotic units to enhance efficiency and safety. These autonomous vehicles will revolutionise the transportation of goods and technicians, navigating to job sites without human intervention and managing their maintenance and repairs to optimise uptime. Drones, in particular, will play a crucial role in inspecting hard-to-reach areas such as power lines and wind turbines, conducting surveys, and performing minor repairs independently. Robotic units will manage a range of field tasks, from repairing complex machinery to maintaining infrastructure, especially in hazardous environments, thereby reducing the risks to human workers.
Work Management systems will evolve to support autonomous decision-making, leveraging vast data from internal operations to adapt business strategies and objectives in real-time, without human intervention. This shift will necessitate a parallel transformation in predictive maintenance, where generative AI will simulate scenarios to predict failures based on IoT data received and recommend pre-emptive actions, thereby minimising downtime, and prolonging asset lifespans. Embedded AI-powered sensors in assets and equipment will continually monitor their condition, enabling self-diagnosis and, in some cases, initiating self-repair.
Integration of AI will necessitate a transformation of the human workforce. Although automation will take over many tasks, human roles will remain crucial, especially for complex problem-solving and tasks requiring nuanced judgment. Workers will need to adapt and upskill, acquiring the skills to manage AI systems, program, and oversee autonomous operations. Augmented reality (AR) will enable remote assistance, allowing technicians to receive expert guidance without the need for travel, facilitating rapid response times and enable faster access to training on-the-go.
Service customisation and integration will see generative AI tailoring services to meet individual customer needs and creating innovative solutions for unique problems. Work Management systems will become part of broader smart city or environment infrastructures, enabling comprehensive management of both public and private assets. This technological shift will lead to labour market changes, with some jobs becoming obsolete and new roles emerging, highlighting the need for upskilling and new regulatory frameworks to ensure safety and AI’s role will extend to strategic decision-making, using vast datasets to make high-level management decisions and real-time adjustments to work plans based on changing conditions like weather or traffic. This will optimise field service operations, marking a significant shift in how work is managed and executed, emphasising the synergy between humans and intelligent systems in shaping the future of Work Management.
In summary, we believe that by 2045 work management and field service management will be highly automated and efficient, leveraging AI, robotics, and autonomous vehicles. AI will not replace humans. Humans will still be needed, especially for tasks that require complex decision-making, creativity, and emotional intelligence. The focus for the human workforce will likely shift towards roles that involve the oversight and improvement of AI systems, strategic planning, and handling tasks that require a human touch. AI, while replacing some aspects of the human field workforce, will create new opportunities and roles that we can only begin to imagine today.
This is not a new concept to human society. With each Industrial Revolution there have been various jobs that have become obsolete, while new jobs have immerged and humans have adapted adequately in each instance, even if there was initial pushback. In 1760 the ‘Spinning Jenny’ was invented, the first mechanical loom. There were 7900 spinners and weavers in the United Kingdom and there were riots over this invention. This new machine would take their jobs, they believed. However, by 1790 the number of spinners and weavers in the UK rose to 32000 because the spinning jenny made yarn cheaper, bringing the price of cotton down and resulting in higher demand for manufactured clothes. Suddenly there was an economic boom because more people could afford manufactured clothes, leading to the increase of supply chains and supply factories, and thus the creation of more jobs. This led to the need for more roads and railways to be built to distribute the clothes, and thus ultimately the first Industrial Revolution.
We have now entered the fourth Industrial Revolution where robotics, technology, AI, and biology are merging in several ways, and much like in the 1700’s, humans become both excited and anxious of the unknown.
These are exciting times where all cities will become smart cities and field services will be highly automated and personalised to the customer’s needs, improving the way that cities, countries, and the globe functions and connects, but that these advancements will not come without their own setbacks related to the navigation of human rights, job loss and ethical considerations of the use of AI.