The AI space is evolving rapidly. One effect of this rapid evolution is that new terms come out quickly that business leaders need to understand, at least to a basic level. In many cases, these terms are not yet quite actionable; there is no product to buy, no team to create, no guidance to issue, etc. However, they are often the industry’s attempts to define the changes that are happening, and within the space of months, convert into developments that require at least reactive action, and may have business benefits to proactive action. As businesses prepare for their next board meeting, here are five terms that the C-Suite should be aware of.
Before exploring each term, let’s quickly cover what they all have in common. First, they are all in the news because the trends they represent are already on the ground and evolving. In fact, the trends have been named, in my perspective, due to the business need to identify the trend and try to understand its impacts. That said, all of these trends are early, and their full form is yet to be seen. The fact that they are in the news is not the key. The key is, for each of them, why they are in the news and why businesses should care about each specifically. We cover this next.
Term 1: Digital Labor
What is it? Digital labor is when AI takes on job roles, managing tasks from software development and testing to customer support, marketing content generation, and more. Also note that a different trend, low-paid gig labor to feed AI models and other infrastructure, is also called digital labor but is not what we are referring to here.
Why will your board care? The potential impact on business is significant. On a positive note, digital labor can dramatically cut operating costs, making it possible to scale a business without a matching scale in human resources investment. However, the addition of AI labor brings new challenges such as security, integration with the human workforce, human upskilling for the new work model, and understanding effective AI use, to name a few. The key question is: does your current headcount plan make sense under digital labor? What will change and why?
What should you know? The state of digital labor is still early. A 2025 MIT report stated that 95% of businesses had yet to see ROI. That said, the technologies are evolving rapidly, and gains, particularly among software firms, are starting to be visible. Finding spots in your organization to explore digital labor integration will give you a foothold of internal experience, help you understand the issues within, and enable you to grow your strategy as trends mature and your internal understanding improves.
Term 2: Agentic Lifecycle
What is it? AI agents are the new model of AI-driven software. Rather than traditional software, which executes predefined tasks in largely deterministic ways, AI agent software can make decisions, plan, execute, and possibly even lead and communicate with other AI agents. The Agentic Lifecycle is to agents what the software lifecycle is to software – the complete management of an AI Agent from its entry into your organization to its exit.
Why will your board care? AI agents create foundational transformations to many business workflows. Employees who previously performed tasks will likely now function as managers of a team of AI agents. Human work will be more focused on task definition, orchestration, and evaluation rather than execution. Correctly managing this transition can benefit the business, while mistakes in transition can lead to lost productivity, increased cost, or other business risks. Meanwhile, AI agents are not free. Managing their lifecycle is a competence unto itself, and one that your organization will need to master. The costs of lifecycle management and associated skills development need to be part of your business plan. The same question can be asked here as with digital labor. Is your headcount plan still correct? Is your infrastructure plan ready for agent lifecycle management?
What should you know? The easiest way to gain experience with agent lifecycle management is to outsource it. For almost any business function, there is now a company selling an agent. These agents may not be the right eventual solution for you, but engaging with a few such vendors can give your team experience with the agentic lifecycle without incurring all the costs and burdens up front. As AI progresses, the build vs. buy question is one your teams will likely need to revisit periodically, so this initial experience will be valuable on that additional front. An alternative is to start a few pilot projects to bring agentic lifecycle expertise into your teams. Either way, keep the use cases as simple as possible and the returns on investment clearly measurable. This is the best way to empower your teams to understand the cost/benefit analysis and take the right steps for business return.
Term 3: AI Tokenomics
What is it? Taken broadly, this is the cost-benefit budget analysis for AI. The term comes from AI “tokens”, a unit of AI operation that most AI foundation model bills (such as ChatGPT, Gemini, Claude) today are based on. It should not be confused with the tokenomics term in cryptocurrency or blockchain. In the AI context, token economics is the necessary practice of understanding the relationship between AI costs and AI-generated ROI.
Why will your board care? AI costs are skyrocketing. Companies that once pushed their employees to use AI, even to the point of tying AI use to promotions, are now retreating to more principled usage tied to ROI. To balance costs while not missing out on AI-related business advances, every company should ask whether its AI strategy understands AI well enough to tie expenses to measurable ROI.
What should you know? There are best practices available to use AI cost-effectively. The primary elements to factor in are: (a) AIs come in a wide range of prices and capabilities. Save the most expensive ones for the most critical and revenue-generating usages. (b) Measure and optimize and teach your employees how to (c ) understand your employees’ AI force multiplier – how to make the combination generate the most value and (d) ensure that business outcomes remain non-negotiable, not AI use.
Term 4: Forward Deployed Engineering
What is it? Started by Palantir, Forward Deployed Engineers are a growing trend, with companies like OpenAI, Anthropic and Amazon investing billions of dollars into their respective FDE arms. FDEs are engineers placed in customer worksites to help them integrate AI tools, Think a local employee but paid for by your AI vendor, with presumably their interests also as goals. In some cases, these FDE ventures are also connected to private equity firms, bringing more companies into the interest pool, some of whom may not be obvious.
Why will your board care? In the immediate, FDEs can be a boon to your business. They can help accelerate AI adoption. However, their interests are not just your business, it is also their employer’s business. How would you manage a flood of these FDEs sitting next to your workers?. Do you have a policy in place to support the interaction? Do you understand the IP risk? Is it possible that the vendor could eventually become your competitor if the AI platform decides to go into your business territory, such as what happened between OpenAI and Apple? Skills transfer from the vendor to the customer is a stated goal of many of these engagements, but knowledge transfer in the opposite direction is also natural from human engagement. Are you in a position to assess the latter?
What should you know? In small numbers, FDEs can be a strategic benefit. In large numbers or in highly sensitive projects, they can be a workforce or business risk. Make sure the projects onto which FDEs are allowed are carefully selected, and their duration (lifecycle) within the team is well managed. If any vendor starts looking like a competitor, or exhibiting desires to enter your business, manage your interactions with them as you would with any competitor. Above all, maintain a multi-vendor approach wherever possible.
Term 5: Taste
What is it? As AI takes over many tasks, what is the key value that humans bring? One such value is Taste, also called domain expertise, instinct, judgement, etc. When an AI can build anything, often faster than a human team, the competitive differentiation is not how fast you can build, but whether you build it at all. While Taste is often described as an individual ability, it also applies to companies. Successful companies have a taste for what their customers want, what works and what does not, in the marketplace, and which problems should be solved and which avoided.
Why will your board care? AI has changed the way companies are valued, internally and externally. With AI, it is safe to assume that any product you introduce can be instantly copied, to the extent that its functionality is visible. What is not visible is the taste of the organization and team that designed it. This taste, however, is also easy to lose; key personnel can easily take their taste to a competitor. It is also challenging to protect legally. You can mandate that an employee not take trade secrets or IP. You cannot mandate that they leave their judgment behind. Are you prepared to protect your Taste resources?
What should you know? The idea that Taste is not just an employee trait but a company trait is still emerging. Knowing it early will give you an advantage. You can take steps to protect your key employees’ retention, and ensure that good taste is shared between teams so that it becomes institutional knowledge rather than individual brilliance.
Putting It All Together
While each of these terms can be assessed individually, they often combine in ways important to business. For example, a FDE can take Taste back to a vendor without any intentional action. Your ability to manage Agentic Lifecycles can affect whether you can execute an effective Digital Labor strategy. Without good AI tokenomics, it will be difficult to implement Agentic Lifecycles or Digital Labor that results in business ROI.
The Non-Negotiables
What all of these ultimately come back to, and likely are important in a board discussion, is the non-negotiable – business ROI. All of these elements have the potential to improve ROI if handled well and present ROI risk if handled poorly. Focus there, and let it become the measurement guardrail that drives everything into place.
