Stop GenAI-ing your customers

Coming off the heels of attending the AWS ExecLeaders event at Pelican Hill, it's clear that Generative AI (GenAI) is in the air.  Maybe a little too much GenAI.

Yes, GenAI is transforming industries, revolutionizing workflows, and driving efficiency. Yet, despite its potential, businesses need to careful directing it at their customers. Why? While GenAI holds immense promise, it also can be dangerous. Examples of bad deployments abound including:

1. Air Canada being held liable for their chatbot's bad advice
2. lawsuits where arguments were based on hallucinated court cases
3. Google's AI telling people they should be eating "at least one small rock per day"

By comparison, when utilizing GenAI internally to optimize business practices—rather than exposing it directly to customer interactions—it can yield better outcomes, safeguard brand reputation, and enhance operational efficiency.

The Pitfalls of Using GenAI with Customers

First, the dangers. They fall into 

1. Lack of authenticity
2. Bad customer experiences
3. Compliance and Legal Risks

Lack of authenticity

Customers crave personalized, empathetic interactions that reflect an understanding of their needs. While GenAI can replicate certain elements of personalization, it lacks the genuine human touch required in complex or emotionally charged situations. Automated responses often feel transactional, leaving customers with a sense of detachment.

For businesses that pride themselves on offering superior customer experiences, relying on GenAI for customer interaction could backfire. AI, while efficient, struggles to fully grasp emotional nuance, tone, and context, which are essential in creating meaningful connections with customers.

Bad customer experiences

Customer trust is paramount in any business. When interacting with AI, customers often have concerns about transparency, authenticity, and accuracy. GenAI’s ability to generate content that mimics human interaction can create confusion, making customers question whether they're communicating with a person or an algorithm. Miscommunications can erode trust, especially when AI-generated responses fall short of addressing nuanced human concerns.

A misstep in customer interaction, such as an insensitive response or factual inaccuracy, can have a far-reaching impact on brand reputation. Even advanced AI models can make mistakes, and when those mistakes happen in customer-facing scenarios, they can damage relationships that companies work hard to build.

Compliance and Legal Risks

Bad experiences can lead to compliance and legal risks—often at scale. Many industries, such as finance and healthcare, are governed by stringent regulations around data privacy, accuracy, and compliance. Deploying AI in customer interactions introduces the risk of unintentional violations, such as providing incorrect or misleading information. AI may not always comprehend the intricacies of these regulations, leading to costly legal consequences if mishandled.

Data privacy concerns are also at the forefront of customer anxiety. With GenAI handling sensitive customer data, businesses must ensure that the AI adheres to strict data protection guidelines. Any slip-up could result in data breaches or misuse of information, damaging customer trust and inviting regulatory scrutiny.

GenAI & Internal Business Optimization

When deployed internally, GenAI has a lot of benefits:

1. Enhanced Operational Efficiency
2. Better Data Insights and Decision-Making
3. Reduced Risk and Controlled Testing

Enhanced Operational Efficiency

GenAI can streamline workflows, automate repetitive tasks, and enhance productivity. Whether it's automating report generation, improving demand forecasting, or streamlining supply chain management, the AI can work behind the scenes to drive efficiencies that benefit the business without risking direct customer interaction.

By deploying AI internally, companies can leverage its strengths to optimize decision-making processes, reduce operational bottlenecks, and free up human talent for more strategic tasks. This boosts overall productivity and leads to cost savings without the external pressures of customer-facing risks.

Better Data Insights and Decision-Making

GenAI’s analytical capabilities can be harnessed to improve internal data insights. From predictive analytics to real-time data processing, AI can sift through vast amounts of information to reveal trends, patterns, and anomalies that are otherwise hard to detect manually.

This can be invaluable for businesses in improving decision-making, identifying new growth opportunities, and fine-tuning operations. By focusing on internal optimizations, companies can ensure that their AI deployments are driving business success from within.

Reduced Risk and Controlled Testing

Internal use of GenAI allows for controlled experimentation. Companies can test AI models in safe, non-customer-facing environments, where any errors or misinterpretations are manageable. This controlled setting is ideal for refining AI’s capabilities before they are introduced into higher-stakes environments like customer interactions.

AI can also help monitor and predict internal risks, whether in cybersecurity, supply chain disruptions, or market shifts. By focusing AI resources inward, businesses can prevent issues before they impact customers, ensuring a more resilient and adaptive organization.

Stop GenAI-ing your customers

While it is tempting to roll out AI solutions to customers in the name of efficiency, doing so may introduce risks that outweigh the rewards. Instead, businesses should prioritize deploying GenAI internally to optimize operations, improve decision-making, and enhance overall efficiency.

By keeping AI in-house, companies can harness its strengths without jeopardizing the customer experience, ensuring that technology serves as an asset for business growth rather than a liability. In a world where customer trust and experience are paramount, AI’s greatest value may well lie behind the scenes.

So for now, stop GenAIing your customer.