The journey to adopting AI in CRM

With Salesforce’s World Tour ongoing across Europe at the moment, there is huge excitement about its vision for AI-powered CRM. There is potential to use machine learning to analyse massive sets of data and make more accurate real-time decisions using AI-automated functions across sales, marketing, and services.

However, Salesforce customers must understand that the journey will be long to achieve this vision. As a global Salesforce partner, Rimini Street provides managed application and consulting services to clients around the world and adopting AI in CRM is top of many clients’ priority lists. Speaking to clients there are the common challenges they face, as well as the four critical foundation blocks, they must put in place to be successful.

Start by building an AI roadmap

The priority, given that this is an ongoing journey and will be dependent on the maturation of AI tools, is to build a roadmap which identifies where an organisation should focus its efforts. A key part of this process is evaluating existing CRM and other core applications to ensure they are set up to embrace AI. Aside from addressing the technical issues around data silos and interoperability, there is also a human consequence. There have already been widespread scare stories about robots taking away our jobs, particularly in marketing and sales, but reality will see AI acting more as a sidekick to support these functions.

Certainly, it will change the way sales and marketing functions operate, but the positive is that it will take away mundane, repetitive tasks. The flipside of this coin is that employee may be uncomfortable that AI will change how they work especially if there are long-established ways of working. It is important to discuss objectives and desired outcomes when adopting AI tools, then it is possible to evaluate how best to implement it alongside the existing core application environment.

This process should be designed to achieve consensus among all employees, so they buy into the vision and journey. In particular, it should clarify which processes in sales and marketing will be prioritised for enhancement using AI. This will manage expectations among employees with a clear plan and timeline. Equally, it is important to allow for experimentation. If employees are able to test the AI tools it will not only broaden their understanding of its potential but reassure them about its capabilities and even open up new possibilities for its use.

Data fragmentation causing a knowledge deficiency

Having laid out the AI roadmap, the next major challenge is consolidating the data layer. Salesforce research from 2023 suggests organisations are using an average of 1,061 different applications. This “API sprawl” creates significant challenges to consolidate structured and unstructured data. Past experience suggests that only roughly 30% of these applications talk to one another, meaning there is a huge knowledge deficiency due to data fragmentation. This complexity also means there are many moving parts between structured and unstructured data, making it harder to distinguish ‘good’ and ‘bad.’ Having confidence that the AI tool is using accurate data to make decisions is absolutely critical.

Don’t rely on leadership in the middle

Another stumbling block is over-reliance on middle managers to implement AI in CRM. Placing all the responsibility on their shoulders only leads to problems, because implementing AI will offer benefits such as automating repetitive tasks, but it will also fundamentally change processes, such as how organisations analyse data. This can deliver competitive advantage, but it also has the potential to disrupt normal business practice and unsettle key employees.

Having worked with clients to integrate AI into their Salesforce environments, there are four common priorities CIOs must consider if AI is to deliver value:

• Start with a master data management. This should focus on delivering a structured data framework and tight integrations to ensure data is structured, accessible and accurate.
• Standards for integration: CIOs cannot overlook how the CRM system integrates with broader ERP stack functions, like supply chain or accounting processes that generate customer-based data. It is critical to analyse these integrations, because without seamless connectivity it will be difficult to scale the use of AI in CRM. The integrations must be standardised, leaving as few data silos as possible.
• Awareness and education of internal stakeholders: An astute CIO will partner with the CFO to drive internal consensus on AI projects. Given the financial implications of adopting AI in CRM, working with the CFO will enable the IT function to educate the business on the impact of adopting AI.
• Get a funding mandate. By educating the business to understand the impact, it will be possible to gain consensus among executives for a strategy that aligns with the available budget.

If organisations put these foundations in place it is possible to move on to the far more exciting conversation of “What could we do?”