AI isn't coming — it's already here, deeply embedded in the workflows of the most productive teams. 

In our latest virtual event, Superhuman's Spencer Grover spoke with Jennifer Lewis, Director of Investment Technology at Vista Equity Partners, and Eliot Gattegno, Chief Learning Officer at Athena. They unpacked how forward-thinking companies are navigating — and leading — the AI-powered future of work.

The conversation centered on insights from our State of Productivity & AI Report 2025 — a survey about how B2B professionals are working today, the role AI plays in their productivity, and where they see the biggest opportunities ahead.

Jennifer and Eliot reflected on the report findings and how AI has been adopted in their companies. They described how AI is transforming their daily workflows, where teams are seeing the biggest productivity gains, and what separates top performers from the rest.

We covered:

• Why the ability to adopt new technology is the top trait managers look for in their employees
• How AI is already saving professionals a full workday per week — and what's needed to 3x that impact in the next five years
• Top-down and bottom-up strategies for scaling adoption across teams (without overwhelming them)
• How "human-in-the-loop" systems can increase productivity while honing decision-making

Top performers are leading the way with AI

Our State of Productivity & AI Report found that top-performing employees are embracing new technology to drive a revolution in work. Top performers are already 14% more productive than their peers — in part because they're using AI more frequently and effectively across core tools like email, messaging, and calendar.

When we asked managers what traits set their highest performers apart, the ability to improve efficiency with new technology ranked higher than work ethic, strategic thinking, and even consistent results.

Leaders are clearly looking to top performers to pioneer the way with AI. But how? That's something both Jennifer and Eliot have prioritized — thinking deeply about how to support employees with a growth mindset towards AI, and drive meaningful, scalable adoption across different functions. 

For teams to see widespread gains, organizations have to make AI approachable, relevant, and useful from day one.

At Vista Equity Partners, Jennifer noted that simply giving people access to AI tools wasn't enough to move the needle. "We found that when we just rolled out tools and hoped for the best, only 1–2% of users became power users. Now we pair every rollout with tactical training, so people see the value on day one."

At Athena, Eliot saw early success by inviting team members to experiment with new AI tools in a low-stakes environment. That grassroots approach led to more sustainable adoption as real use cases emerged from the ground up. "People want to adopt new tech when they can see how it benefits them. We made it less about mandates and more about experimentation."

So while top performers may be the early adopters, their success can't scale unless leaders build the conditions for it — with clear support, visible use cases, and a culture that rewards curiosity.

AI is already saving time — but the real upside is still ahead

Our survey found that AI is already saving B2B professionals at least one full workday per week — more than 50 reclaimed days each year. But the opportunity doesn't stop there: most respondents expect a 3x increase in productivity over the next five years, with some leaders projecting even more dramatic growth.

Where will those gains come from?

The immediate opportunity is in automation and better focus in core workflows. With teams spending more than half their workday in email, messaging, and calendar tools, major gains can come from where you're already working. 

Jennifer shared an example of how Vista's deal teams leverage AI with Superhuman and other tools during deal evaluations. "Our deal teams aren't drafting investment memos and then summarizing that investment memo to put it in an email to attach the investment memo. [There's] so much duplicative work that if AI can reduce that duplication — being able to summarize and get the uptake faster is huge."

Both Jennifer and Eliot imagine that the biggest productivity leaps in the near future will come from making better decisions, faster.

At Vista Equity Partners, Jennifer and her team are focused on exactly that. By embedding AI into early-stage deal analysis, they're accelerating the pace of review and reducing time spent on unqualified opportunities.

Jennifer noted, "We're building use cases that help our deal teams get to a faster yes — or a faster no. That means spending more time on the right deals, and less on the wrong ones."

At Athena, Eliot shared how AI is reshaping not just what gets done — but who does it. By combining executive assistants with AI-powered workflows, he's been able to confidently delegate more decisions, freeing up time for higher-value work.

The result? AI becomes more than a time-saver — it becomes a growth multiplier, helping teams focus energy where it drives the most impact.

AI doesn't replace human judgment — it enhances it

While automation is powerful, both Jennifer and Eliot emphasized that the real value they've seen is from "human in the loop" systems — with AI supporting human decision-making.

At Athena, Eliot has operationalized this philosophy through a system he calls Executive Daily Focus — a structured, repeatable process that combines AI-generated summaries, pre-drafted responses, and assistant-led prioritization to optimize delegation and dramatically reduce time spent on low-value tasks.

It's part of a broader approach Eliot describes as training on both fronts: helping team members leverage AI for efficiency, while simultaneously investing in distinctly human skills like leadership, motivation, and communication.

Jennifer echoed the importance of this balance, saying, "AI can’t replace judgment, but it can provide better data to support it." Her team is actively exploring ways to use AI to improve data accessibility and reduce time-to-insight — especially in deal evaluation — but always with a human making the final call.

The takeaway? As AI takes over repetitive or time-consuming tasks, the value of human discernment only increases. Top teams are designing systems that amplify both — and in doing so, they're multiplying their impact.

Start with the use case, not with the tool

Both Jennifer and Eliot emphasized that simply giving teams access to AI tools isn't enough. They've found that defining clear use cases, relevant context, and tangible outcomes, has led to the most useful and effective adoption of AI tools.

To drive real adoption, Jennifer and her team now take a hands-on, prescriptive approach — one that focuses on immediate value and practical application.

Jennifer noted, "We call it the bear hug approach: here's a tool, here are three ways to use it, and here's why it matters to you."

The bottom line? Successful AI adoption isn't about what's possible — it's about what's useful, today. Teams should start with specific workflows tied to their core business outcomes, and build momentum from there.

Final thoughts: start now, scale deliberately

AI is no longer optional. It's not enough to simply wait for shiny new tools — teams need to intentionally embrace AI in their core workflows or get left behind.

Leaders need to support their teams today with the best AI in core workflows and with culture change — via training, defined use cases and goals, and an intentional approach to automation and AI-assisted decision making.