The Human-Centric Approach to AI in Sales CRM: Enhancing, Not Replacing, Sales Relationships

Nikolaus Kimla, the Founder and CEO of Pipeliner CRM, shares his commentary on mastering a human-centric approach to AI in sales CRM, how it can enhance sales relationships, and more. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

2024 was the year of AI implementation, from major retailers to CPG manufacturers and more. Businesses across industries are implementing AI solutions and changing how they operate. That includes sales. AI-powered CRMs are reshaping the sales landscape. They serve as a supportive, augmentative tool that transforms routine and rote tasks like data entry and sales forecasting so that salespeople can spend more time doing what they do best—building meaningful, lasting relationships.

However, with AI use comes a level of ethical responsibility and a need for increased security while maintaining the level of human touch needed to be successful.

Ethical Considerations of AI in Sales

Companies should evaluate the ethics of their approach when using AI. As with any new, up-and-coming technology, there’s a temptation to superficially integrate AI into tech stacks by linking to AI applications, but this raises some serious ethical considerations.

AI systems can perpetuate and amplify existing biases if trained on partial data or designed with a particular worldview. Therefore, companies leveraging these models must exercise due diligence to avoid perpetuating singular viewpoints or other prejudices. These unintentional biases can have ripple effects, limiting opportunities and alienating valuable potential customers. Transparency is needed to prevent this, as AI systems can be complex and difficult to understand, making explaining their decisions and actions challenging.

Businesses must diligently audit their AI systems for potential biases before engaging with AI, whether constructed in-house or by a third-party vendor. They must also maintain regular monitoring to identify and mitigate any instances as they emerge.

Securing Your Data

To maximize AI’s potential in sales, businesses must give AI access to vast amounts of customer data. This introduces new responsibilities regarding data security, as some or all of this data may be sensitive and require added protection. A data breach or misuse can create mistrust among customers and may even result in lost sales in the long term.

To prevent this, businesses must evaluate their security practices at every stage of AI implementation. This could include tactics like encrypting customer data, establishing clear guidelines for data access controls, conducting regular audits, and monitoring in real-time to proactively identify and address potential vulnerabilities. It should also include adhering to data privacy guidelines like GDPR and CCPA. When in doubt, there is no such thing as too much precaution.

Businesses must also be transparent with customers on their data security and usage. Be upfront about how customer data is used, how it’s stored, and how customers can access or delete your access to their data at any given time. In addition to being the most practical, strategic approach to data security, this level of transparency helps establish trust and improve customer rapport, both essential in sales.

Keeping the Human Touch

Sales are inherently relational, and the nuances of each customer interaction often demand a level of judgment that only a human can bring. Maintaining human-in-the-loop protocols ensures that AI supports rather than replaces the essential human element of sales.

For instance, at Pipeliner, we see AI as supportive and augmentative rather than a replacement for human interaction in our business. We communicate that with our clients. Our goal in providing them access to AI technology is to remove routine, redundant, and low-value (but necessary) tasks from the day-to-day for sales professionals, allowing them to spend more of their time building relationships and engaging meaningfully with their customers and prospects.

While AI cannot replace the human touch in sales, it complements it by streamlining mundane tasks and providing actionable insights. This balance allows sales professionals to focus on building meaningful customer relationships, armed with the tools and data needed to engage more effectively and efficiently.

Benefits of AI in CRM

Despite the additional ethical and security considerations associated with AI use, businesses shouldn’t be deterred from exploring the benefits. For those teams willing to consider and accept the potential added ethical and security burdens of using AI-powered CRMs, there are already several strong use cases, including personalization and automation.

AI-powered CRMs can provide sales teams with a comprehensive view of each customer by analyzing behaviors, preferences, and interactions across channels in real-time. This enables highly personalized experiences at scale. Additionally, through predictive analytics, AI can anticipate customer needs, identify upsell and cross-sell opportunities, and flag potential issues in customer relationships, allowing sales professionals to address concerns proactively.

For automation, sales CRMs can enhance lead generation and pipeline management by enabling businesses to scale their efforts while maintaining personalized communication. Streamlined pipeline management simplifies tracking and eliminates repetitive tasks like data entry, freeing sales teams to focus on closing deals and driving revenue. Modern platforms further optimize efficiency by integrating all tools within one system, reducing errors and distractions.

Striking a Balance

True progress and balance lie in discovering how AI can support human capabilities rather than supplement them. When implemented thoughtfully, AI-powered CRM solutions can significantly improve workflows and equip sales teams with insights and time to improve customer relationships. Before jumping headfirst into embracing this next wave of tech, businesses need to be proactive in understanding the ethics behind how AI is trained and the security behind the system they plan to use. They must also establish clear guidelines for company use and maintain a human approach.