How AI Completely Shifts the CRM Software Value Proposition

Johnny Grow

From CRM and AI to AI Powered CRM


  • Artificial Intelligence (AI) for CRM has transitioned from futuristic hyperbole to a practical and proven technology that is making salespeople, marketers and customer service agents more successful.
  • AI transitions CRM software from a customer data depository to a predictor of customer behaviors, creator of customer insights and facilitator of customer and company objectives.
  • AI and CRM are more than a convergence of customer data and analytics processing, they are a synergistic relationship which shifts customer engagement from reactive to proactive and elevates data from a byproduct to an asset.

AI can predict and recommend actions that achieve outcomes important to the customer and the company.

AI algorithms sift through large volumes of data to surface important information and make recommendations or decisions more quickly and accurately than people.

When staff integrate AI into their daily work processes, they make more timely and better decisions, and the company achieves a sustainable competitive advantage. It's sustainable because making better and faster decisions never loses its value.

From a more technical perspective, AI uses machines to simulate human intelligence and carry out tasks with or without human intervention. Computer processing intelligence is the ability of machines to analyze, understand, learn, predict and dialogue with people or other machines.

AI includes many supporting technologies, such as natural language processing, machine learning, robotics, predictive analytics and other software apps which answer questions, deliver insights and make recommendations.

AI Technologies

From a CRM software perspective, the purpose of AI is to better serve the customer and in turn deliver better customer experiences, grow the customer relationship and achieve other objectives that serve both customer and company.


Three drivers that will further propel AI use in CRM software include the following.

  1. The accumulation of even more customer data from more channels
  2. The democratization of AI tools within CRM software that shift AI design, development and operation from data scientists to business analysts or power users; and
  3. The strategic benefits and payback generated from delivering superior customer experiences

CRM systems hold a treasure trove of customer data.  However, there is such a thing as too much data, or at least more data than can be manually processed.

For over two decades CRM software has been focused on collecting and storing customer data. CRM systems deliver tactical reporting such as meeting minutes and short-term sales forecasts but have mostly failed to convert data into actionable insights that make staff more productive and customers more satisfied.

AI within CRM software is changing the status quo in a very big way. It's ability to analyze large volumes of customer data, spot anomalies or trends, and deliver actionable insights to the staff who are empowered to deliver better customer experiences or make better decisions is truly a quantum leap in the CRM value proposition.

AI within CRM software transitions a company’s data from a byproduct to an asset.

CRM and AI Strategic Benefits

In a report commissioned by Salesforce, the global market intelligence firm IDC found that AI with CRM software has already delivered a revenue impact of $120 billion with $33 billion of it from improved productivity alone.

At a company level, a McKinsey report titled, Customer Experience: New capabilities, new audiences, new opportunities, found that companies that harness customer data for insights achieve revenue gains of 5-10 percent and reduce costs by 15-25 percent within two to three years.

CRM with AI benefits include efficiency-based cost savings and improved staff productivity. However, the more strategic benefits include using data to identify customer behaviors and align company actions to increase customer engagement, grow customer relationships and improve products and services.

The AI and CRM Path to Success

If you plan to take advantage of the combined benefits of AI and CRM, consider the three most strategic steps of promoting a decision support culture, prioritizing objectives and identifying high impact role-based use cases, such as sales AI use cases, marketing AI use cases and customer service AI use cases.

Promoting a culture that understands how to benefit from data, insights and supplemental intelligence is a precursor to any AI technology adoption. Culture starts with employees that recognize the need for descriptive intelligence to better understand what has happened, diagnostic intelligence to understand why it happened, predictive intelligence to find patterns and see what is likely to happen, and prescriptive intelligence that helps them understand the best solutions to solve a business problem or achieve a business objective.

A small group of analytics-savvy staff can help the organization extend the use of analytics to a broader set of users. Many companies formalize their analytics driven culture in a data driven operating model (DDOM).

The actual implementation of AI with your CRM software starts with clear objectives and recognition that any successful CRM AI project has a business-first focus and is based on measurable business outcomes that align with the company's priorities.

A Design Thinking workshop is the most accelerated approach to surface and prioritize the highest impact business outcomes. These objectives become the measurable success factors to demonstrate AI project success.

The objectives identify what to accomplish. Then use cases spell out what needs to happen.

The challenge of creating data-driven intelligent solutions is less about technology and more about applying technology to solve business problems that matter. Stitching data together to build an AI algorithm or data model is an important task but completely dependent upon the right use case.

Below are the most cited CRM AI use cases based on an IDC report titled, AI/CRM Economic Impact.

AI Use Cases

See the most cited Artificial Intelligence use cases for CRM software based on an IDC report titled, AI/CRM Economic Impact.

Click to Tweet

To organize and add context to use cases, Gartner analyst Michael Blechar recommends companies adopt an information capabilities framework. We've standardized on this type of framework to support multiple types and categories of use cases and make repeated use of a common set of interfaces and technologies. We typically create use cases in agile user story formats so that they have specific business goals, stated beneficiaries and clear acceptance criteria.

It's easy to get confused when selecting the right AI applications. Our experience has been that there are three technologies that make the best entry point for most use cases.

  • Machine learning – these services are really just complex mathematical formulas that sift through large volumes of data to find anomalies, detect patterns and make real-time recommendations such as what offers, promotions, content or engagement to deliver to a prospect or customer. Popular CRM systems such as Dynamics 365 and Salesforce offer simple but extensible machine learning services that can be adapted based on your objectives and use cases.
  • Natural language processing (NLP) – this technology uses text or speech recognition with data models or algorithms to respond to user questions. This makes AI extensible to the masses. Anybody that can ask a question can get a data-driven response.
  • Predictive analytics – these models and algorithms extend the trajectory of data to deliver forecasts and recommendations with confidence levels. They shift CRM analytics from hindsight to foresight.

Something novel about AI is that the insights and recommendations get better as you accumulate more customer data in your CRM system and adapt the algorithms based on learning. This technology is one of the few that gets better with age.