AI, Enterprises Still Laying Foundation to Effective Machine Learning

In an era where artificial intelligence (AI) is not just a buzzword but a transformative force, companies stand at a pivotal crossroads. Imagine a world where your company can predict customer needs before they arise, tailor experiences to individual preferences and streamline operations. This isn’t a distant future – it’s the reality of today’s hypercompetitive marketplace, where companies are facing a clear choice between reinvention and decline.

That said, most organizations are barely dipping into the potential value that AI can deliver. AI can revolutionize industries, disrupt traditional business models and drive unprecedented growth; however, implementing AI systems without a clear strategy for integration and iteration will not yield the desired results.

AI is becoming integral to every aspect of businesses – strategies, customer offerings, capability systems, managing risk and preserving value. And yet, PwC’s 2024 US Responsible AI Survey found that only 38% of organizations have deployed AI in both employee and customer systems. As AI rapidly becomes a natural part of how businesses operate and grow, it can bring disruptive change to every industry.

This requires a shift in mindset, where companies need to ask themselves how AI can change their value proposition, revenue streams and cost structure. From there, business leaders must make critical choices about technology and architecture, product and service offerings, their workforce and advantages over their competitors to protect market share and profitability. By reimagining fundamental aspects of their models and integrating AI into their core operations, companies can pave the way for a smarter workforce and deliver enhanced value to stakeholders.

The technology is especially relevant for companies looking to enhance their customer relationship management (CRM). By leveraging AI, companies can create new business models that leverage data-driven insights and automation to predict customer behavior and personalize experiences at scale.

Why Continuous Innovation Matters

To thrive in the modern business landscape, leaders should understand and embrace continuous reinvention to thrive in the modern business landscape. According to PwC’s 27th Annual Global CEO Survey, top companies are focused not only on their business model but also the operating and technology models that enable it—and they do so continuously.

By continually integrating the technology’s insights into their CRM system, companies can maintain and enhance the performance, relevance and effectiveness of its applications. This continuous process enables ongoing learning and adaptation to change, making AI smarter over time.

An AI-powered CRM system can streamline operations and help drive more value through:

  • Personalized customer experiences: AI can analyze vast amounts of customer data, including purchase history, browsing behavior and demographic information. By understanding individual preferences, AI can tailor product recommendations, marketing messages and special offers to each customer. This level of personalization enhances the customer experience by delivering relevant content and recommendations, increasing customer satisfaction and driving repeat purchases.
  • Predictive analytics: AI algorithms can analyze customer data to identify patterns and trends, enabling companies to anticipate customer behavior and needs and offer relevant products or services at the right time. For example, AI can use past purchase history and browsing behavior to recommend related products, offer personalized discounts or suggest complementary items. This level of predictive analytics enhances the customer experience by proactively meeting their needs, increasing customer loyalty and driving additional sales.
  • Sentiment analysis: AI can analyze customer interactions across various channels to discern sentiment and emotions, allowing companies to address customer concerns, provide timely resolution and improve overall customer satisfaction. Additionally, sentiment analysis can help companies identify trends and patterns in customer feedback, enabling them to make data-driven improvements to products, services or customer support processes.
  • Customer segmentation: AI can segment customers based on various criteria, such as purchasing behavior, demographics, geographic location and preferences. This analysis helps identify distinct customer segments with similar characteristics and behaviors, allowing companies to tailor their marketing efforts, communication strategies and product offerings to each segment’s specific needs and preferences, ultimately increasing customer satisfaction and driving revenue growth.

Keys to Adoption

Reaping the benefits of AI goes beyond simply implementing the technology, especially as it relates to CRM. It requires alignment between the workforce and AI so that they can make data-driven decisions to help improve the customer experience.

As a first step, companies should invest in training programs to upskill employees on AI and its applications, equipping them with the knowledge and competencies needed to effectively implement, use and innovate the technology. This not only maximizes the return on investment in AI but also fosters a culture of continuous improvement, responsible use and strategic alignment within the organization.

By integrating AI into the daily workflows of employees, companies can gather real-time insights and observations, which can then be used to improve and refine AI algorithms. This creates a feedback loop of continuous learning that enables AI to deliver increasingly valuable insights and employees to enhance their decision-making for CRM.

As AI becomes integral to all facets of business, the key to adoption and success will be trust. Trust is earned, and businesses can help build it through Responsible AI (RAI), including strong data governance. A responsible data foundation that clearly defines and documents how data is collected, stored and used is critical to deploying and scaling AI. As such, companies should implement policies to manage data privacy, security and compliance and measures to detect and mitigate biases in AI models. Establishing these guardrails helps build trust among stakeholders, including customers. PwC’s 2024 US RAI Survey found that enhanced customer experience was the top benefit organizations achieved or expected to achieve from investing in RAI practices.

One of the biggest barriers to the adoption and value realization of AI at an enterprise level can be data quality. Customer data is difficult to harness, as it can exist across multiple platforms across an organization, comes from various sources and is structured in varying formats. Companies should establish a robust data strategy that defines what information they need from customers to provide personalized experiences and services, how they can get it (and if they need customer consent to do so) and where they can store it.

The Bottom Line

To go from good to great, companies should view AI transformation as an ongoing journey rather than a destination. By continuously pushing the boundaries of AI, companies can unlock their full potential and deliver even greater value and experiences for customers. The time to reimagine, innovate and make AI intrinsic is now – the possibilities are limitless.


Reggie Walker, Partner, Global Salesforce Alliance and Competency Leader, PwC U.S., also contributed to this article.