How AI Is Revolutionizing Customer Relationship Management

Artificial Intelligence is revolutionizing the way businesses engage with their customers. By leveraging generative AI (GenAI), shaped by a company’s unique data, companies can accurately discern customer sentiment and intent. This enables them to curate compelling experiences that not only enlighten but also contribute to enhancing customer satisfaction.

Companies are, no doubt, excited about the potential benefits of GenAI, but the real work comes down to reimagining the ways they work, using GenAI and their own data to securely integrate AI into their processes. A new survey of business leaders in the US shows that 88% struggle to capture the value from their technology investments. 

While customer data is one of the most valuable assets in an organization and key for executives looking to unlock insights that drive transformation, customers are demanding that it needs to be treated responsibly. And this comes down to trust.

Customer Data Is Decentralized, Unstructured and Redundant

While plentiful, customer data is extremely difficult to harness. It sits across multiple platforms across the organization, comes from a variety of sources and is structured in varying formats (if it’s structured at all). It sits in CRM platforms and in marketing engines. It is generated by sales, service and help desk interactions. And it is spread out in different departments, geographies, business units and infrastructures spread across the world.

GenAI can work with this data, especially the messy, unstructured data that makes up so much of a company’s customer data. It can be used for segmentation and personalization to deliver positive experiences. It can power self-service to speed time to resolution. And it can improve the productivity of employees and streamline operations to deliver cost savings at scale. Arming human workers with AI-driven insights, such as through autonomous business development representatives, combines human reasoning with the speed and accuracy of machines.

AI Is Only as Good as the Data You Feed Into It

However, incomplete or redundant data sets can lead to inaccurate results, bias and other undesirable outcomes, essentially eroding customer trust in your AI models. If customers don’t trust how you manage and use their data, they’ll be reluctant to share it with you, further degrading AI results. It’s a vicious cycle that could be difficult to turn around once customer perceptions of your brand go south. Trust is something that businesses must continuously earn. Customers need to know that their data won’t be misused, sold to the highest bidder, or leveraged to spam them with irrelevant experiences.

It is important that customers implement process controls to help support customer data in being used ethically and within the parameters outlined in customer agreements. However, while these developments are a step in the right direction, responsible AI ultimately comes down to the business using the data.

Here are three things organizations should consider as they leverage customer data and CRM to help power positive experiences:

1. Invest in building a responsible data foundation

Building trust starts on day one of any AI or big data initiative. Organizations need to think about their relationship with customers and how they can continuously earn their trust so they can have access to the data they need to power these interactions. Make sure you have a true enterprise-level definition of how you think about your customers. What do you need from them to provide superior experiences and services? How can you get this information? Do you need consent? Where can you store it? And how can you ensure responsible access to stakeholders across the organization? Once you define your data strategies, you can then start to consider how to use them to empower segmentation and personalization strategies to deliver the kind of experiences your customers deserve and expect.

2. Engage all parts of your business in GenAI

AI, and specifically GenAI, has the power to radically change how you interact with customers and conduct business, and innovation shouldn’t be constrained or siloed. Having people from different departments and job functions involved in data use policies surrounding GenAI development ensures a wide variety of expertise that can lead to surprising results. However, it’s important to put multidisciplinary teams in place that can manage and regulate responsible AI initiatives across your organization. While it’s important to encourage experimentation, you don’t want rogue AI projects going on without company knowledge. AI implementation can be extremely valuable, but only if there is a consolidated effort and buy in from business leaders. Just as important, there needs to be a human element overseeing the process to make sure the quality and output is still in line with business expectations.

3. Think big but within the bounds of progress

The most important recommendation is to push transformative progress. AI is a disruptive technology that has the power to change every aspect of human society -- from how we interact with each other to how we get from point A to point B. The future is unlimited, but it’s going to take truly revolutionary thinking to get us there. Encourage and engage your innovators and give them a safe way to apply GenAI to enable new ways of working. Make sure they have access to the data they need to experiment, iterate and, ultimately, dream big. Encourage wholesale changes in how things are traditionally done rather than slow and measured step-by-step progress. Quick wins that reimagine processes and make incremental improvements can be helpful with getting buy-in from the top and increasing budgets, but going after low-hanging fruit hardly moves the needle when it comes to big change. Customers are ready to be wowed with new experiences that help them speed up and enrich interactions with their favorite brands. Be revolutionary and have fun thinking about ways to move your business and society forward.

The Road To Good Data Governance

Customer data sourced, managed, and orchestrated by AI and fed into next-generation CRM solutions has the power to radically change how brands interact with consumers. But with great power comes great responsibility. Organizations need to gain trust with customers, continuously proving to them that they are using their data in a responsible manner. This includes delivering streamlined, personalized experiences that are relevant and in good taste. Organizations need to build a responsible data foundation that dictates how data is collected, stored, and used. While AI innovation requires the democratization of AI, these processes need to be centralized with a multidisciplinary team from across the organization that can formulate policies and ensure good governance. Only then can organizations unleash their greatest thinkers to radically change customer experiences, the way it does business and society as a whole.