Intel
The AI revolution is on the horizon, but it remains extremely challenging for business leaders to set direction, vision, and develop solid plans. However, we can provide some relatively indisputable insights into current and future capabilities that can help you begin to build a complete picture of this revolution. These include:
Also, welcome to the AI revolution: from horsepower to human power to machine power
AI has already achieved impressive results in its generative and predictive capabilities, and it will continue to improve. There is a huge investment and enthusiasm in this field that is not likely to slow down anytime soon. CEOs are always looking for ways to achieve more (growth and margins) with less. Many jobs (or parts of jobs) are candidates for reallocation to AI resources because they are routine, procedural, or algorithmic in nature. According to the Harvard Business Review (September-October 2024) by H. James Wilson and Paul Daugherty, most business functions and more than 40% of all work activities in the United States can be augmented by AI. New companies will soon be AI native, which means they will not hire humans in the first place unless they have to. These companies will likely show the public where humans are still valuable and where they are not. And we will follow suit (although at different speeds depending on the company).
Building on this imperfect but relatively stable foundation, we were inspired by the “Six Levels of Driving Automation” created by the Society of Automotive Engineers to develop a framework that reflects the evolution of AI capabilities and how they will impact enterprises over the next decade or so.
Over the next decade, a series of continuously improving AI resources will have a two-fold impact on business and the human workforce: First, AI will have a far-reaching augmentation effect, taking over low-value tasks and allowing humans to focus on more strategic and creative work.
But perhaps in five years or so, AI will begin to take over entire work roles, starting with the most “procedural” or rule-based jobs, and eventually gain enough decision-making and orchestration capabilities to take over entire teams and even business units.
These two distinct effects, known as the augmentation and displacement phases, are expected to occur gradually at first and then rapidly, although the speed and depth of adoption will vary across industries, functions, teams, and individuals.
Six levels of autonomous work
King and Afshar – co-authors
Six levels of autonomous work
Below is a row-by-row explanation of the graph above.
Level: Each autonomous work level is given a number (0-6) and a title. The title indicates the amount and complexity of work that the AI can do at that level. It's essentially a general breakdown of work, starting with the smallest and simplest chunk of work, or task (Level 1). The next level up from task is subprocess (Level 2), which refers to a group of tasks that are typically performed sequentially to complete a discrete part of a business process, such as ensuring that all relevant information is accurately and completely collected to open a customer case.
At Level 3, the AI has the ability to complete business processes such as taking customer orders, managing customer cases from start to finish, qualifying leads, etc. At Level 4, the AI completes multiple processes from start to finish, performing most of the work traditionally assigned to roles such as sales representatives, marketing specialists, and service agents. We focus here on general commercial operations, but the same is true for manufacturing and all other types of operations.
And to help your company get the most out of AI, here are four things to tell your board:
At level 5, AI or AIs can perform most of the roles associated with any commercial team, including a “manager” and his or her direct reports running one or more complex business processes. At level 6, AI can coordinate the work of multiple teams, functions, and processes traditionally organized as a business or business unit. Ultimately, this will include all small and medium-sized businesses, and in the long term, large enterprises (although “large” refers only to the complexity of the business and the size of revenue, not the number of employees).
Phases: The six levels of autonomous work outlined above do not represent a linear trajectory for AI. AI will not advance to more senior roles within an organization like traditional career progression. Instead, there are two very distinct phases in its progression. The first, levels 1-3, is the augmented phase, where digital assistants enable human employees to do what they do best while also creating new opportunities.
The second, levels 4-6, is the replacement phase, where digital agents take on increasingly larger and more complex responsibilities from humans and begin to replace them over time.
The Role of AI: Here I will explain the main functions of AI and how it interacts with its human colleagues at different levels. This is from a non-technical perspective. If you are interested, I will follow up with a deeper technical perspective on each level, but for now I wanted to focus on the relationships.
AI will change every business, but most leaders aren't ready
Human role: This is the flip side of the AI role, again focusing on the relationship between humans and AI, and their relative responsibilities and capabilities.
Adoption: This is the date by which mainstream adopters (broadly including both early and late adopter categories) are expected to start applying AI at each level. Innovators and early adopters will be sooner, and late movers will probably be slower unless the crisis changes their trajectory.
We know that adoption rates vary across industries and departments. Even at the employee level, adoption is unlikely to be smooth sailing. Some will embrace AI with enthusiasm, but they are more likely to embrace an AI that frees them from the monotony and tedium of their jobs than one that promises (or threatens!) to do the more creative and strategic parts.
Others will likely push back against all of this, especially those who fear their jobs will be completely replaced by AI, but broadly speaking, we are already seeing examples of both predictive and generative AI being applied across most industries, and we know that more sophisticated and capable bots and agents are on the way.
How autonomous work impacts business
We have identified three key business implications of this evolution in AI: We encourage leaders to recognize that these impacts are coming soon and start planning accordingly.
Augmentation and Replacement Plans: First, as we have already noted, the six levels do not represent a linear trajectory for AI. Rather, there are two very clear stages in its evolution. The first, levels 1-3, can be described as the Augmentation stage. Most commentators focus on this stage because it is indisputable and reassuring. Research suggests that AI could automate most tasks in knowledge-based professions by 2030, dramatically increasing the productivity of the average worker. Humans will be augmented by AI, freeing them from manual, repetitive, and boring tasks to focus on strategic and creative activities. AI could also create new opportunities for humans at this stage.
But this may obscure the reality of what's coming next: When AI reaches level 4, it will enter the replacement phase. As AI becomes capable of performing roles autonomously, it will no longer follow traditional career progression. It will not be promoted into a role that supervises or manages the humans performing those roles. Sooner or later, AI will replace humans. And when that replacement happens, it will happen rapidly. Current HR and change leaders need to start planning for this now.
SUDA Business Management Model – Boundless Company
King and Afshar – co-authors
Accelerated Responsiveness: AI helps accelerate the operational cycle of any business. In our 2023 book, Boundless, we introduced the SUDA model (Sense, Understand, Decide, Act) as an operating model for business in the AI era. AI enhances the sense, understand, decide, and act capabilities of any business, and those that do will have an advantage over their competitors. Businesses will be able to make more informed decisions faster, and in doing so, they will gain what the military calls decision advantage and superiority (more on this in future articles).
What's crucial here is that a company's success depends on shortening the time between each stage of the SUDA model, and driving the gap between sense and act as close to zero as possible. Each level of the autonomous work model represents an improvement in AI capabilities at one of the four SUDA stages, as well as a general acceleration across the model in decisions and actions at different scales, from the minute-by-minute activities of individual employees to end-to-end business processes to strategic enterprise-wide initiatives. AI accelerates and amplifies both stages and scale. Companies that cannot shorten the gap between sense and act will lose to those that can.
Exceeding human capabilities: AI will not simply become more productive compared to a human full-time employee (FTE) or measured in human power units (as discussed in a previous post on AI, horses, and humans). At levels 5 and 6, AI will demonstrate the ability to handle situations that exceed human capabilities. AI will then be measured in machine power, perhaps as a function of complexity, accuracy, and speed, rather than simply GPU/CPU or transactions per second (TPS).
Leadership Call to Action
AI is coming and it's already here. Leaders need to recognize that AI isn't going away, even if the current level of hype is unsustainable. Even if leaders aren't yet ready to embrace AI itself, there are some things they can do to prepare, including good business practices.
A company-wide or enterprise-wide data strategy can be designed and implemented (ideally extending to the business network). Data is and will always be a big topic, with or without AI. You can also focus on streamlining key business processes and be smart about eliminating, simplifying and standardizing them before bringing in AI to enable and drive them (again, this should be done with or without AI). HR and transformation teams should also plan for both phases of AI, before AI is introduced and it's too late.
Also: Leadership Alert: The dust will never die down, but generative AI can help
Finally, while AI may seem like a problem to solve, as we discuss here, it is also a key part of the answer for navigating increasingly uncertain and volatile times. AI can play a key role in helping leaders and their teams make strategic, data-driven decisions and take effective action.
These are exciting times, and we hope our model helps provide leaders with enough structure to take action amid all the uncertainty and ambiguity.
This article was co-authored by Henry King, a leader in business innovation and transformation strategy and co-author of Boundless: A New Mindset for Unlimited Business Success.
