To say AI sales enablement tools are transforming the B2B sales landscape is a wild understatement.
Productivity increases?
Turning huge datasets into actionable insights?
Better pipeline management and stronger forecasting potential?
Productivity increases?
Shorter sales cycles?
From automating and leveling up prospect outreach, to injecting dream-like levels of personalization, to providing real-time, contextual prospect data, to helping reps anticipate prospect objections, to reassigning administrative tasks and data-crunching, AI is assuming responsibility for huge chunks of the sales process.
It’s not just a transformation—it’s a revolution.
Balancing Risks with Rewards of AI in Sales
But just how to incorporate AI into business and workflows to realize the promise of AI – responsibly – is proving complex for many organizations for many reasons.
At MarketSource, we’re anxious to bring the benefits and promise of AI to our customers, but because we manage sales functions for organizations including global brands and Fortune 500 companies, we cannot afford to adopt irresponsibly. We have to be careful that any AI tech we use doesn’t end up in the ChatGPT world but instead lives behind a firewall that protects both us and our clients.
Many of our customers are simply not in a position to pivot and take advantage of emerging tech, let alone vet, justify, and adopt it – especially tools that have developed at the incomparable pace of AI. These brands come to us for peace of mind. We do a lot of work behind the scenes, such as identifying use cases by collaborating with business experts and developing proofs of concept, to show our clients what’s possible with AI while we’re protecting their data.
Our customers aren’t always able to pivot quickly and take advantage of emerging tech—especially tools that have developed at the incomparable pace of AI. We do the heavy lifting behind the scenes to explore what’s possible with AI—all while protecting their data. For their sake, we make sure any new tech we consider both meets our performance and innovation standards and that we stay clear-eyed about and have a plan to mitigate the risks.
They also come to us because they lack the resources, bandwidth, and expertise to vet and choose optimal tech that makes things better—not worse—for them. We’re structured to analyze and vet new tech rapidly, filtering it through multiple customer and sales motion use cases.
It’s one thing to evaluate and implement the right tools. It’s quite another to deploy it effectively to your sales force, encourage adoption, foster consistent use, and ensure ongoing training. It’s no wonder sales organizations are struggling to keep up and adapt.
As we explore in our blog series, seller adoption of tech tools is notoriously difficult. New tech like AI, even though it will make their jobs easier in many ways, is often confusing and overwhelming to sellers. And with much being made of how AI is going to replace many sales roles, it’s understandable that AI uptake is low.
According to McKinsey’s latest B2B Pulse Survey of B2B decision-makers, 19% of respondents are already implementing gen AI use cases for B2B buying and selling, and another 23% are in the process of doing so. That said, most B2B leaders have yet to embrace generative AI or even engage with it.
For our customers’ sake, we must make sure any new tech we consider both meets our performance and innovation standards and that we stay clear-eyed about and have a plan to mitigate the risks.
Because they count on us to do the necessary due diligence, to lead them through foreign, overwhelming terrain, and to guide them to success, we must always be one or two steps ahead of our customers. We need to be out in front of every innovation. To use a sports analogy, we like to say we need to be where the puck is going. For AI to benefit them, we have to explore, vet, and implement new AI tools aggressively so they don’t get left behind, but with caution so we don’t put them at risk.
A Cautiously Aggressive Approach to AI Sales Enablement
AI in sales is super provocative, bleeding edge, and we’re already seeing how it can be a profound differentiator when it comes to increasing the skill and acumen of our reps.
But there’s only so much we can figure out right now—responsibly.
Which is why we’re taking a cautiously aggressive approach as we continue to learn and keep up with what seems like weekly AI advances.
What does a cautiously aggressive approach look like?
“On every front, we need to be one or two steps ahead of our customers. AI is no exception.”
– Steve Bonvissuto, Vice President of Innovation, MarketSource
Our approach today is less about what we’re doing now than learning as much as possible and how our learnings position us and our customers for the future.
It means a commitment to exploring emerging AI technologies—prudently, from all angles, then harnessing them in ways that push us forward. That evolve our already innovative tech stack to make sure we stay on the leading edge and maximize return for our clients. That don’t even sniff in the realm of harming them. It’s less about what we are able to do now, and more about where we will be a year from now as a result of our learnings.
After all, we’re on our clients’ front lines, interacting with their customers, supporting their teams, and integrating with their systems. We can’t afford to be reckless or waste their resources, but we are in the business of maximizing their opportunities. We must be judicious, but not afraid.
Any tech we consider has to pass through a formal, rigorous vetting process. From there, we conduct a proof-of-concept pilot in a small environment. Only if we get satisfactory results will we adopt it.
For example, of the dozens of Salesforce instances we use to service our customers, we’re initially limiting our application of advanced AI capabilities like bots and leveraging large datasets to analyze and predict results to a handful of accounts, with an eye toward rolling it out more broadly.
AI Sales Enablement on the Ground
The initial aim of AI was to increase productivity. While that’s still relevant, we’re focused on exploring AI use cases that magnify our sellers’ skill, acumen, and effectiveness, helping them:
- Become well-versed in products more quickly
- Respond more effectively/expertly to prospect/customer objections/questions
- Practice and refine pitches
- Personalize customer outreach and communications
We’ve been immersing ourselves, experimenting, piloting, and when appropriate, deploying. Most importantly, we’ve been learning – pushing the boundaries of what AI can do for our sellers and our clients they serve.
We’ve also spent the last two years pushing our technology partners to give us access to their AI tools so we can learn how best to apply them to empower our sellers. We’ve been collaborating closely to explore the limits of what AI can safely do and aligning that with our principles and tech-forward approach to sales.
For example, we’re mid-pilot with Salesforce for multiple customer engagements. They’ve made an aggressive push into AI with Agentforce, which, among other things, prompts Salesforce to give us information from our database, allowing us to become much more knowledgeable about the impact of our work and predictive so we can course-correct.
Through our parent company, Allegis Group, we were one of 600 companies globally who participated in Microsoft’s Early Adoption Program (EAP) for Copilot, an AI-powered tool that uses natural language processing and machine learning to help users be more productive, creative, and collaborative. As an EAP participant, we identified potential use cases and gathered feedback that guided Microsoft’s AI investments. Among other things, our reps use Microsoft Copilot to craft highly personalized, contextual prospect outreach, making engagement more effective and allowing them to focus more of their time on selling.
Within 90 days, any new rep we hire is working in Allego. AI and leadership can review any content that is relevant keyword searchable and can assess the user’s knowledge. We use role-play scenarios to prepare our sellers for difficult or important meetings, all of which AI and leadership score using rubrics. Sellers can choose the level of difficulty of their buyer, the sales methodology they want to practice, and whether to anticipate customer objections.
If we’re calling on a prospect, we use AI to glean contextual information from social media and create personalized outreach and messages.
Beyond these uses, we’re exploring applications such as AI language models that help reps become more versed in products much faster. Like AI-based cue card systems that help them learn about the features and benefits of the products they’re selling, where they’re scored on their responses.
We’re also looking at other customer simulation tools that allow reps to practice a pitch as many times as they want and then send it to their manager for scoring and feedback. This helps them hone their messaging, become more audible-ready, and prepare to be their best in front of the customer. And we’re one of the first to use AI-generated cue cards to assess our reps’ knowledge of the products or services they’re selling on our customers’ behalf.
All these moves maximize our productivity, knowledge, and efficiency, which means our customers get to their goals—faster.
AI in sales is changing by the minute, and we know we’ll have to evolve our strategy with the landscape and our clients’ morphing needs. In the meantime, we have the structures, systems, mechanisms, frameworks, processes, and experts to explore both the power and pitfalls of AI – dependably.
Until the path becomes more illuminated, we plan to continue taking a cautiously aggressive approach to exploring AI as we help our clients navigate these ever-changing waters.
Ready to talk?
Author: Steve Bonvissuto
Steve Bonvissuto leads our innovation team to continuously improve the delivery of MarketSource services, creating more value for customers and employees. Steve consults and partners with key internal and external executives to innovate and execute strategies that enable teams to deliver additional value and exceed customer expectations. Proven engineering principles are used to streamline and improve sales processes. Steve is responsible for evaluating, piloting, and selecting emerging sales enablement technologies for increased efficiencies.
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