Why Successful Agentic AI Adoption Begins With Honesty and Good Data

While AI has exploded in popularity among consumers, and many companies embrace it for customer service, adoption lags in B2B deployment, especially when it comes to sales and marketing. Only 16 percent of B2B companies currently use predictive analytics or plan to implement intelligent forecasting tools in their sales, studies show, while nearly a fifth see no role for AI in their organizations at all. 

But B2B firms can no longer afford to ignore or sidestep the issue; AI is set to become a major element in business, and companies that don’t keep up will lose out. This is increasingly the case with the growth of agentic AI, which can autonomously take over many daily tasks as well as advanced projects and strategizing for sales and marketing teams. Teams can use agentic AI to respond to leads, set appointments, make follow-up calls to customers or potential customers, send email reminders and file reports.

AI agents can also respond to customers on their own terms — whether automatically translating received and sent messages to and from any language, or contacting customers and dealing with their issues in tandem with their time zones, thus ensuring the highest level of customer satisfaction possible. Furthermore, agentic AI can pursue leads, engage with new prospects, analyze data on potential customers and design campaigns to reach them. 

Studies show that B2B companies relying on human staff without using AI agents were significantly slower in responding to leads, with nearly a fifth never even bothering to answer emails. The reasons for hesitation on B2B adoption of agentic AI are understandable and could include concerns that AI will disarm them of their greatest asset, direct connections with customers, as well as discomfort involved in adopting and keeping up with new technology, and, of course, the costs involved. In addition, there are questions about whether the ROI on AI investment is really worth the effort, as well as a lack of guidance on where to start. But done right, agentic AI can be a time-saver, a money-saver — and even a job-saver.

Be Honest About AI Use

When a business decides to implement AI that involves agents and client-facing automation, it is essential to inform people they are indeed interacting with an AI agent and not a human. This honesty has two practical benefits, including the fact that often, people are more honest and direct when they know they are talking to AI, studies show. This, in turn, allows companies to gather information more quickly and more efficiently. 

In addition, being honest about the use of AI agents increases positive feelings about the company among its customers and partners. According to one study nearly  60 percent of B2B buyers prefer dealing with AI agents, at least at the beginning of the sales process, as long as the firm is clear about its use of agents. A firm that uses AI, and is upfront and honest about it, is perceived as more efficient, enabling more intuitive, reliable and usable data and interactions. 

Savvy B2B customers realize that when AI systems handle much of the routine work in a sales relationship — gathering information, setting appointments, providing the answers to specific questions — human sales people are more available for other more complex interactions or conversations that cement a relationship. Indeed, one new study shows that AI shortens the B2B sales cycle by a week on average, helping them close more deals and keep their customers happy.

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First-Party Data Is the Biggest Piece of the Puzzle

For AI to work effectively, models need to be able to deal with a firm’s specific issues, and to be trained on data relevant to those objectives. This is often a challenge for B2B firms, especially smaller ones, which are likely to have a relatively small roster of customers. As a result, B2B organizations’ AI models that predict customer behavior, market trends, and effective campaigns often lack the requisite data, and as a result, fail to perform as effectively as expected.

The good news is that the amount of data needed for training AI is dropping, along with related costs, partly because new models can be trained on smaller data sets, a method demonstrated by DeepSeek, which was able to build a powerful model based on smaller data sets than usually used. Those companies seeking to build and use AI models should focus on homing in on only the most important and relevant data and focusing just on the specific tasks they need. Customers will also likely become more willing to allow their information and interactions with the company to become part of the AI training process if the company is honest about the use of data and AI.

A company’s past calls and emails from clients are excellent sources of data for training models. That data is already in the company’s possession, and of course, is very relevant to determining customer needs. AI systems that can search patterns can determine, along with ongoing needs of their customers, general trends in their industry or in the market. This enables them to not only craft more relevant and effective methods of working with current customers, but to develop methods of reaching new customers and markets, as they develop campaigns that target the proper market segments.

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Create a Small and Focused Agentic AI Plan to Start

For many B2B companies considering implementing AI in sales and marketing, it’s a question of how to start, and for that, they need a plan. Like with most things, it’s best to start small, initially implementing AI systems in specific areas or with specific teams concentrated on a limited number of responsibilities and goals. At the same time, when companies introduce AI, they should approach it as a big picture transformation — not just a task-focused time-saver, even though it may very well feel like that initially. For organizations that have the manpower, appointing someone to oversee the implementation of AI in B2B tasks can be helpful.  

In addition, companies need to address concerns by staff, including the common fear that they will be replaced by AI systems. The opposite is actually likely to be the case; AI will empower staff and enhance their capabilities, making them more effective than ever. AI can free up salespeople to do the job they were meant to do – build relationships with customers, and help fulfill their needs using their company’s products or services. Most companies want to work with other companies that “demonstrate a strong human element” – especially later in the sales funnel. With AI doing much of the routine work, sales teams will be able to work on expanding the organization’s reach and footprint.

Implementing agentic AI in sales and marketing will have positive ripple effects throughout a business,  especially when companies are upfront about their use of agents and deploy them well. It will help companies grow and scale more quickly, reach new markets and retain customers and clients. 

B2B customers want quick responses from firms at all levels of the sales funnels, and many will change vendors simply because response wasn’t quick enough. AI is a game changer for this challenge, helping prevent leads and queries fall through the cracks and prevent clients from leaving, the key to maintaining and growing any business.