In this recap article, we'll look at the strategies, lessons, and practical use cases that are helping enterprise sales teams get more value from AI agents today.
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There's a lot of noise around AI in sales right now. Whether it's researching accounts, writing emails, summarizing calls, updating your CRM, or coaching reps, AI seems to be making its way into every part of the sales process.
And the question isn’t whether AI belongs in sales anymore - it does. The real question is whether it’s making reps more effective.
During a recent webinar discussion with revenue leaders from Hootsuite, and QAD Redzone, we explored how enterprise sales teams are putting AI agents to work, where they're seeing the biggest impact, and what it takes to make those implementations successful.
In this recap article, we'll look at the strategies, lessons, and practical use cases that are helping enterprise sales teams get more value from AI agents today.
Over the past few years, companies have been racing to adopt AI. From adding copilots, to experimenting with generative AI, and rolling out AI agents, the goal was to figure out where AI could eliminate repetitive work, improve productivity, and help sales teams move faster.
Initially, that experimentation was necessary because organizations needed to understand where AI fit into their workflows, and where human judgment was still essential. But now, it’s about results.
“Whenever we’re looking at tools or introducing agents, I bring it back to what my objectives as SVP of sales are,” says Lawrence Green, SVP of Global Sales at QAD Redzone."When looking at tools, I ask, 'Does it increase ARR? Does it increase the average deal size? Does it shorten the sales cycle? And does it improve the buyer experience?'"
Those are important questions for revenue leaders to ask because it’s easy to get caught up in the latest AI announcement or feel pressure to roll out another AI tool. But at the end of the day, buyers don't care how much AI you're using. They care whether they're having a better buying experience. And leadership cares whether it's helping the business grow.
If your AI results aren't what you expected, the problem may not be the AI itself. It may be the data behind it.
"I've certainly experienced this myself... we've rushed to launch an agent, or maybe put Claude Enterprise in place, and then suddenly you realize the context stack underneath it, the data that we've got on Salesforce, the structure of that isn't necessarily in the format that we need it," explains Lawrence. "I've had to slow down to go faster in some respects."
Taking time to fix your data is important because it’s easy to assume AI will solve all of your operational problems. But the reality is, it’s just going to amplify whatever you give it. So if your CRM is full of incomplete records, outdated contacts, or inconsistent opportunity data, your AI outputs won't be much better.
The bottom line here is that before you invest in another AI tool, make sure you can trust the data before it.
AI is raising the standard for sales execution not by replacing reps, taking over, or working 24/7. It's doing it by making it realistic to consistently execute the best practices that often fall by the wayside when time gets tight.
Think about stakeholder mapping, documenting meeting insights, or building account plans. None of those are new ideas. Sales leaders have preached about them for years. But when you're managing dozens of deals with a never-ending to-do list, something has to give. More often than not, those best practices get reserved for the biggest opportunities.
But AI is changing that. Now, best practices can be done with very little effort from reps, thereby raising the standard of execution.
Take stakeholder mapping, for example.
"I hated doing this manually for my deals," says Ross Rich, Co-founder and CEO of Accord. "This is definitely a requirement for any considered purchase." Using AI, reps can quickly generate a stakeholder map using CRM data, conversation intelligence, and publicly available information. It can even identify people mentioned during sales calls and recommend where they fit within the buying committee.
Amanda Mitchell, Senior Manager of Sales Operations at Hootsuite, immediately saw the value in this. "They [the reps] don't have to go source all these people," she says. "They get one lead, they find one person, and now all of this mapping is done. I found this to be one of the most impactful agents you all [at Accord] brought to the table."
The impact doesn't stop with sales. Customer success teams inherit a complete picture of the account, including who the champions are, who makes the buying decisions, and who influenced the deal along the way.
Lawrence believes that matters more than ever, stressing that, "since everyone has access to the same information, it's become even more important to clearly articulate and visualize the value of your product. As the sales process unfolds and new stakeholders join the conversation, AI helps us automatically capture and update that information instead of leaving it in someone's head."
The best AI doesn't try to replace a salesperson's judgment; it gives them better, more accurate information to work with.
That's the philosophy behind Accord Agents. Instead of trying to sell for the rep, they surface recommendations, organize information, and automate repetitive tasks. The rep still decides what to accept, what to change, and what to ignore.
One of Amanda's favorite parts of Accord Agents is that it keeps the rep in control."It uses that conversational intelligence, but then allows for the rep to accept the suggestion. So you still have a human element to the AI. They can adjust and they can make changes."
In practice, that means reps can:
"The ability to accept recommendations is far, far more seller-friendly than simply telling them exactly what to do,” says Tim Bolton, Senior Director of Sales & Marketing Operations at Hootsuite. “Having those recommendations there helps reps stay on top of their tasks and gives them the flexibility to leverage AI while not letting AI drive their workflow."
The benefits of this include:
In enterprise sales, this is where AI is having the biggest impact. It's helping reps do more of what works, more consistently.
One of the biggest opportunities for AI is in improving what happens after the deal closes.
For many enterprise organizations, customer handoffs are still manual. Information gets scattered across Slack messages, CRM notes, PowerPoint decks, and call recordings. By the time implementation or customer success takes over, they're often piecing the customer story back together.
AI has the potential to change that. Instead of losing context every time ownership changes, stakeholder maps, business objectives, meeting insights, and deal history can move seamlessly from sales to implementation and customer success.
That's one of the capabilities revenue leaders are most excited about. Today, many handoffs are still done manually, so having a centralized place for that information "is going to be key to maintaining customers,” shares Amanda.
As AI continues to mature, it won’t just help sales teams sell faster — it will also help every team deliver a better customer experience.
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