If you’re reading this, you’re most likely aware that AI will have a role in the way your team looks and works in the future. The question is – are you bullish on it, or bearish?
Our take on it at Agent.ai is that AI is a powerful tool that can augment human talent rather than replace it. Dharmesh Shah–co-founder of HubSpot, AI thought leader, and Agent.ai’s fearless leader–puts it simply: “A.I. replaces tasks, not people.”
Instead of viewing AI as competition, view it as a collaborator. Shah suggests you can either compete against AI, or compete with AI. When you use AI as part of your toolkit, you get better outcomes.
That doesn’t mean AI won’t replace elements of roles. That’s because AI excels at automating rote tasks–the repetitive, time-consuming work that doesn’t require creativity or empathy. By offloading drudgery to AI, your team can focus on high-value activities. This gives humans time for human-focused work: building relationships, solving complex problems, and innovating.
In other words, AI frees your team to excel at the uniquely human aspects of work. Let’s explore what that might look like for you, a leader in your organization, and how you can build a team that excels with AI instead of fighting against it.
Many employees fear that AI might make their roles obsolete. A great manager turns this fear into empowerment by reframing AI as a team enhancer.
To do that, you must address the common fear, “AI is going to replace me,” openly. First, remind your team that in the short to mid term, AI automates tasks, not jobs. Roles that involve creativity, empathy, and complex decision-making are less at risk–in fact, those roles stand to benefit the most from AI assistance.
Second, let your team know that they might be underestimating themselves–but you’re not. Shah highlights a quote by Microsoft’s Vice Chair Brad Smith: “People who think that a machine can do everything that a person can, I think they’re underestimating people.”
Even as AI gets smarter, humans have irreplaceable qualities formed by our experiences and values. Just because a machine can do something doesn’t mean people will want the machine to do it. Often what we see in work is just the output–but that output is a direct result of the experience of achieving it.
Take performance reviews as an example. An AI could analyze an employee’s performance and create a review. But the experience of working with an individual and delivering a review to that individual is not an experience we can remove humanity from. (Well, we can, but no one would want to–despite how painful as some performance reviews may feel.) Discussing a person’s performance at work requires nuance, empathy, understanding, and experience, something that an AI cannot replicate.
Managers can reassure teams that human experiences and connections matter, and AI is there to enhance outcomes, not erase the human element.
By fostering this perspective, you create a culture where the team isn’t bracing for AI to take over, but rather looking for ways to leverage AI to excel. When employees stop seeing AI as a threat, they can start seeing it as a helpful teammate.
You can begin by reinforcing human value. If a team member initially interprets “You are competing with AI” as competing against it, guide them to see it as competing alongside AI–using it as a tool to get ahead. This shift in thinking can turn anxiety into enthusiasm.
By way of example, let’s say your employee is training for a marathon but they keep getting rashes at their waistband from the chafing. The chafing is painful and it slows them down. You tell them hey, if you put Vaseline on your waistband it’ll prevent chafing. Would they do it?
Of course they would. Vaseline is just a tool to make them a better runner. It’s not going to run the race for them. But it may help them run a little faster, a little better.
AI is just a tool to make them a little better, a little better. It’s not going to do their job, because it’s not human. (Just like Vaseline doesn’t have legs and can’t run a race.)
Next, encourage a growth mindset around AI. The best way to learn how to use AI is to make AI feel less alien by integrating it into daily work. When AI suggestions are part of brainstorming sessions or routine workflows, your staff will start to view them as normal support, just like software or the internet.
I recommend referring to your AI tools as “assistants” or “agents”, to continue to quell any anxieties about AI replacing team members. They are meant to be tools to make your team stronger, and are not equivalent in value to your actual team.
While your team learns how to leverage AI through use, continue to regularly highlight examples of where human judgment made a positive difference that AI alone couldn’t. This reinforces that your team’s expertise is crucial.
For example, AI can supply information about a prospect, problem, or company instantly–but only a human can truly empathize with each unique situation. Rather than trying to out-know an AI, top performers out-care and out-connect the competition. AI can furnish the data and even draft initial communications, but your team adds the personal touch and understanding that builds relationships, closes deals, solves problems, and creates loyalty.
If your team is more data-oriented, reinforce that yes, AI can analyze huge data sets without breaking a sweat. It can even spot patterns your team might miss. It’s your team’s business judgment that decides what to do with those insights, though.
For example, an AI tool might flag that a certain project is behind schedule by analyzing task updates, but a project manager will use experience to reallocate resources in a sensible way.
AI provides the “what,” humans decide the “how”--a combination that leads to more informed and balanced decisions.
Crucially, using AI to amplify strengths also boosts team morale. Employees start to feel less like cogs doing monotonous work and more like innovators and problem-solvers. Their uniquely human contributions become more visible, and their roles can be redefined to include more interesting duties. This is how you, as a manager, can help with job enrichment, skill development, and career growth. (Imagine a financial analyst freed from manual spreadsheet consolidation that can learn to use AI forecasting tools, instead!)
As your team harnesses the power of AI, it’s your job as their leader to highlight successes. Call out instances where AI played a supporting role, and a team member’s skills delivered the win.
For example, “Our AI research assistant delivered sales battlecards before each call, and thanks to Jane’s preparedness in those meetings, we closed 20% more deals this quarter.” This reinforces the idea that AI + human together drives better outcomes.
As a team leader, it’s your job to ensure your team is on the forefront of new developments–and AI will soon be the “thing” everyone needs to know:
“In a couple of years, building an AI agent will be as prevalent and common as building a web app is today,” Dharmesh Shah
Forward-thinking managers who get their teams comfortable with AI now will position their organizations to grow faster–and those that don’t risk being left behind.
We’re entering “the age of the AI agent”, where AI tools (or “agents”) become standard for solving business problems. From automating workflows to generating creative content, these agents can tackle a wide variety of use cases across departments. This means every team–whether technical or non-technical–has the potential to benefit. And early adopters will have the advantage.
Think of AI skills as the new computer literacy. Just as early adopters of the internet or mobile tech gained a competitive edge, teams that quickly integrate AI into their operations will outperform those that lag. Emphasize to your team that learning to use AI is an investment in their future success (and the company’s).
On the flip side, ignoring AI isn’t a safe strategy. There’s risk in staying idle. The technology is evolving rapidly, and competitors who embrace it can leap ahead (and then lap you). The question isn’t if AI will impact your business, but when and how significantly. In other words, managers don’t have the luxury of a “wait and see” approach—proactive exploration is key to not getting left behind.
Your team may suffer from blank canvas syndrome if you ask them to start embracing AI. It’s your job to come to them with some ideas on how to leverage AI.
At a high level, AI can help teams do more with less and do things better than before. Consider areas where your team has bottlenecks or untapped opportunities, and there’s a good chance AI can help. Here are some areas of focus to get you started:
AI tools can dramatically speed up workflows. For example, an AI scheduling assistant can handle meeting logistics in seconds, or an AI document parser can pull out key insights from hundreds of pages. The result is your team gets more done in the same amount of time, accelerating project timelines and output.
AI’s analytical capabilities can improve work quality. A software team using an AI code review agent might catch errors that human reviewers miss, leading to more robust products. A content team using AI for proofreading and SEO suggestions will produce publications with fewer mistakes and better reach. Higher quality work strengthens business growth by improving customer satisfaction and trust.
AI might reveal patterns or suggestions that spark innovation. For instance, an AI trend analyzer might indicate an emerging customer need that none of your competitors have addressed yet. Your team can then develop a new product, solution, workflow, or service for this niche. In this way, AI not only optimizes current operations but also helps identify where to grow next.
Sales reps often spend hours researching prospects or preparing for calls. AI agents can handle much of this prep work. For example, Agent.ai has a company research agent that creates comprehensive company reports in seconds. Instead of manually gathering a prospect’s industry, size, recent news, and so on, a rep can get an AI-generated brief and walk into a meeting fully informed.
Another task perfect for AI is scanning data to find potential leads. Agent.ai’s marketplace highlights a prospect extractor agent that identifies and verifies leads from conversation logs or databases. This agent can quickly suggest new contacts or accounts to pursue, filling the top of the sales funnel with minimal human effort. Your team spends less time list-building and more time actually engaging with qualified prospects.
An AI agent could draft personalized outreach messages or sales emails by analyzing prospect information. For instance, if an AI knows a lead’s company just launched a new product, it could include a congratulatory note and a tailored pitch in the email. While reps should review and tweak AI-generated notes, this assistance allows one salesperson to effectively customize communication for dozens of prospects in the time it used to take to write a handful of emails.
AI can serve as a diligent assistant that reminds account managers, customer service reps, or sales reps to follow up with clients, logs call notes, and updates CRM records automatically. These administrative tasks often eat up a person’s day. With AI taking care of record-keeping and reminders, your team can devote their energy to what actually generates revenue: understanding and addressing customer needs.
Today, AI tools can generate articles, social media posts, video scripts, and more from just a prompt or source material. Shah shares an example of a YouTube-to-LinkedIn Post agent that he tried: You feed it a recorded video or webinar, and it automatically generates three different LinkedIn posts summarizing the key points. This kind of capability means your team can repurpose content quickly and fill the content calendar without starting from scratch every time.
A smart AI writing tool doesn’t just churn out words; it can tailor content for the medium and audience. AI content generators can be instructed to emphasize certain keywords for SEO, match brand voice, or target specific demographics. Think of it as having a junior copywriter or editor on call 24/7–one who knows your style guide and can produce infinite drafts. Your team can then refine the best outputs, rather than writing everything from square one.
Staring at a blank page is almost everyone’s nightmare. AI can help brainstorm ideas of all sorts–campaigns, titles, team outings, whatever it is you’re stuck on.
For example, if your team needs ideas for a new product launch tagline, an AI could generate 20 variations in seconds. These suggestions can spark the human creatives’ imagination, who can then mix and refine the ideas into a winning concept.
The AI provides the raw materials that creatives mold into gold.
Modern marketing often involves personalization–tailoring messages to different customer segments or individuals. Doing this manually is labor-intensive, but AI is well-suited to the task. AI can analyze customer data to create micro-segments and then generate personalized content for each (such as individualized email subject lines or product recommendations).
A human can oversee this process, defining the tone and rules, while the AI does the heavy lifting of customizing content for thousands of recipients. The result is a highly personalized marketing approach that would be onerous if not impossible to achieve by hand.
Whether you’re in ops, strategy, marketing, or elsewhere in your organization, AI tools can quickly analyze metrics, customer behavior, and market trends to provide insights.
For instance, AI might sift through your website analytics and find that a particular blog post is converting exceptionally well, or that a certain demographic is interacting more with your ads. These insights help the team double down on what works and adjust strategy fast.
Instead of waiting for an analyst to crunch numbers over days, AI can deliver actionable intel in real time.
AI can act as a guardian of your brand style and quality. Tools powered by AI can automatically proofread content for grammar and spelling, ensure the tone matches your brand voice, and even check that images or layouts adhere to brand guidelines.
This reduces the back-and-forth between writers, designers, and editors. Your team can move faster from idea to publication because AI is catching errors and inconsistencies early.
Management is often working in a cross-disciplinary function. With that can come struggles with siloed information and coordination challenges. AI can act as a connective tissue in such situations, ensuring everyone has the information they need and smoothing handoffs between different specialists. This is also an excellent opportunity for you, as a leader, to practice what you preach and find uses for agentic AI in your own workflows.
Here are some ways you can use AI as a bridge to different teams within your organization.
In cross-functional projects, each discipline (be it engineering, design, marketing, etc.) has its own knowledge and jargon. AI can help aggregate knowledge from all corners and present it in a digestible way to everyone.
For example, an AI agent could be tasked with reading all project documents–technical specs, marketing research, design briefs–and answering team members’ questions in plain language.
Ask it, “What are the top priorities from the design perspective?” or “Summarize the customer requirements we discovered,” and it can pull from all sources to provide an answer. This prevents miscommunication, keeps everyone on the same page without requiring constant meetings, and prevents other teams from coming to you with constraints you didn’t know existed that requires your team members to backtrack on work.
Cross-disciplinary teams often have many meetings to sync up. An AI notetaker (an AI tool that transcribes and summarizes meetings) can be invaluable for this. It will record the discussion, pick out key decisions, action items, and points of concern for each department, and share the summary with the whole team. If an engineer misses the marketing part of the meeting, they can quickly read how it impacts them.
AI ensures institutional memory persists beyond the meeting and remains accessible to all disciplines.
Each specialty has its own “language”. Data scientists might talk in terms of algorithms and p-values, while salespeople talk about pain points and closing deals.
AI models (like large language models–or LLMs) are actually quite good at translation. Not just between human languages, but between styles of writing. You could use AI to translate a data-heavy report into a one-page executive summary for non-technical teammates. Of you could have AI turn a legal contract you have to read, but don’t understand, into a bulleted list of key points for your project manager. By doing this, AI acts as an interpreter, making sure expertise in one domain is understood by all others.
Project management tools increasingly have AI features that predict roadblocks or suggest task assignments. In a cross-functional team, AI can analyze the project plan and identify dependencies (e.g., it might alert that “Task X by engineering might be delayed because it’s waiting on Task Y from design”).
It can also optimize scheduling by quickly crunching who is available when, across departments, to suggest the fastest timeline. Essentially, AI can serve as a project coordinator for you that never gets tired of updating the Gantt chart. This keeps the multi-disciplinary effort moving smoothly and ensures your team remains properly resourced.
Sometimes different departments are hesitant to step into each other’s domain. Introducing collaborative AI tools can ease this by providing a neutral ground.
For example, if Marketing and Engineering are collaborating on a product improvement, an AI tool that both can query (say, an AI that answers questions about customer usage data) gives them a shared reference point. They can both trust the AI’s data and then discuss together, rather than debating whose data or perspective is “right.”
In cross-disciplinary efforts, aligning on process is tough – each team has its way of doing things. AI can help here by observing patterns and suggesting best practices.
For example, if an AI observes that whenever design hands off specs in a certain format, engineering starts development faster, it can recommend that format consistently. Or it might notice that when customer support is looped into development discussions early (via summarized reports), the final outcome has fewer issues, prompting an automated suggestion to include support in those discussions. These subtle insights can improve how the team works together over time.
Single Source of Truth: With AI, you can create a dynamic “single source of truth” that all team members can query. This might be an AI chat interface connected to your project docs, emails, and data.
Ask it any question about the project and it responds based on all available information. This reduces the confusion of different versions of documents or misaligned information. The AI always pulls the latest, consolidated info. Team members from any discipline can rely on it for quick answers, which speeds up decision-making and alignment.
To fully realize AI’s benefits, managers must invest in training and upskilling their teams. This doesn’t mean everyone needs to become a data scientist or AI engineer.
Rather, it’s about building AI fluency–comfort and proficiency in using AI tools and understanding their outputs. Dharmesh Shah outlines a simple three-part strategy for organizations to stay effectively informed and adept with AI without feeling overwhelmed.
1) Use AI daily. Don’t just study it, actually use it. The best way to learn AI is by using it in everyday work. Encourage your team to incorporate AI into routine tasks, even in small ways. For example, have them try an AI tool to summarize long emails or draft a first pass of a report. This hands-on experience teaches more about AI’s capabilities and limitations than a bunch of articles or seminars could.
Over time, your team will develop an intuition for what AI can do, where it struggles, and how to get the best results from it. This is AI fluency–similar to gaining fluency in a language by daily practice.
Tip: Provide your team with access to a variety of AI tools (many have free versions). Maybe one day a salesperson uses ChatGPT to brainstorm responses to a customer, while a project manager uses an AI scheduling assistant, and a marketer experiments with an AI image generator for ad creative. In team meetings, let members share quick demos of how they used AI that week. This normalizes AI usage and spreads knowledge organically.
2) Schedule regular AI brainstorming sessions. Make it a habit to periodically review how AI could solve your team’s biggest challenges. Identify the top 3 problems hindering your growth, then brainstorm if any new AI solutions have emerged to address them (or if you could build an agent that would address them).
AI technology changes fast. What wasn’t possible a few months ago might be possible now. By reviewing challenges regularly, you might discover that a new tool or feature can partially or completely solve an issue that your team has been tolerating. Even a partial AI solution can deliver substantial benefit if it tackles a significant pain point.
3) Explore new AI tools with purpose. Every week there seems to be a new AI app or feature announced. Rather than trying them all aimlessly, have your team test new tools on specific, real-world problems.
For example, if a new image-generating AI is released, a designer on your team might experiment with it to create a logo idea for an upcoming campaign (a concrete task) instead of just seeing what random art it can make. This focused approach does two things: It shows you quickly whether the tool is useful for your needs, and it keeps your team’s exploration productive, not distracting.
Additionally, you can keep a “not yet, but soon” list for AI. Teams sometimes try an AI solution, find it’s not mature enough, and then write it off. Instead, log those near-miss cases, and revisit this list periodically. AI tech improves quickly, so what didn’t work a year ago might now be viable. This habit ensures you eventually capture value from AI breakthroughs as they happen, rather than falling behind because you ruled something out too early.
Harnessing the power of AI to grow your team ultimately comes down to leadership and vision. Your goal as a leader should be to neither act as an AI skeptic who ignores the tech, nor an AI fanatic who chases every shiny object.
But regardless of your industry, some level of AI adoption is increasingly critical. Providing a positive, secure growth mindset for your team–and adopting these upskilling and exploration practices–will ensure your team is ready to harness AI in ways that genuinely moves the needle for your business.
The outcome is a team that's continually evolving, using AI to amplify their abilities, and never falling into complacency as the tech landscape advances. WIth AI acting as the connective thread weaving your employees and tools together, you’ll have a team that’s greater than the sum of its parts.