Over the last several weeks, much has been written about the potential impact of AI on established enterprise software companies. Markets have been rattled, and iconic legacy technology firms such as Oracle and Salesforce have experienced considerable volatility in their stock prices. The private credit markets have also been shaken as investors in private credit funds grow increasingly concerned about the long-term viability of privately held software firms to which they have extended credit.

Investor anxiety is largely centered on AI’s ability to rapidly create new products that could potentially replace legacy platforms or dramatically compress profit margins.

As someone who leads a company that develops mobile and cloud-based enterprise software for fleet management, dispatch, scale operations and point-of-sale systems in the bulk materials industries, that perspective shapes how I view the current conversation around AI.

Why Enterprise Software is Different

Enterprise software is fundamentally different from consumer software. In the consumer world, switching to a new shopping, ride-hailing or food delivery app because it is better or offers incentives is relatively simple. The transition creates little disruption, costs almost nothing to implement and may even generate short-term economic benefits. At most, the user simply needs to learn how to navigate a new, relatively straightforward application interface.

Replacing enterprise software, however, is an entirely different matter.

Completely changing a company’s ERP system such as NetSuite or Sage, or swapping out a CRM platform like Salesforce, can require years of effort. Depending on the size of the organization, it may involve significant technical resources, retraining staff, operational disruption and millions of dollars in investment. Most importantly, management must be convinced that the new AI-driven product will deliver meaningful and measurable benefits: cost savings, improved operational efficiency, enhanced safety, and expanded margins, so that the return on investment justifies the risk.

It is naïve to assume that simply introducing a “shiny new” new AI-powered solution guarantees adoption.

For companies that develop scale management and point-of-sale (POS) software, it takes time to convince customers using legacy platforms such as AgVantage, OneWeigh, PC Scale and SMS Turbo to upgrade to newer systems, even when those customers know their current platforms are aging, unsupported or technologically outdated.

The reason adoption takes time is straightforward: change is often difficult. Retraining staff requires effort. Operational workflows must be adjusted. There is always a natural concern about disruption and the unknown, particularly in mission-critical environments where downtime carries significant financial consequences.

Communication Matters More in the AI Era

This reality highlights the central point of this article: In the age of AI, communication with customers has become even more important. Migrating customers to AI-driven platforms requires more communication, not less. Even though companies may provide the most sophisticated AI-driven software, the trusted relationships built between sales professionals, customer success teams and their customers remain essential.

Likewise, when organizations undertake major technological transitions, they rely on trusted advisors who understand their operations, constraints and business goals. Perhaps in five to 10 years this dynamic will change. When leaders become more comfortable conversing with and trusting AI to make decisions, the use of AI agents and chatbots could become a substitute for human communication to guide managers’ decision-making around replacing legacy systems. For now, however, human interaction remains essential. Companies, including TruckPay, spend significant time working with customers to explain the benefits of modern platforms. Equally important, they must be careful not to overpromise.

It is critical that customer-facing teams be honest about what AI can and cannot do. Claiming dramatic productivity improvements, such as an overall increase in programmer productivity of 300%, or implying that legacy platforms can be instantly modernized when that is not realistic, undermines credibility.

Likewise, it is important to acknowledge that new platforms, while innovative, may not yet replicate every feature that has evolved over 20 to 25 years of industry experience.

In the bulk materials industries, much of what exists in legacy systems reflects decades of accumulated operational knowledge. AI can certainly, and likely will, accelerate development and help close feature gaps faster than ever before, but it will not happen overnight. Portraying AI as an overnight cure-all is unrealistic.

Alongside great products, great service remains essential. Some software firms that emphasize their use of AI believe customer support can be handled primarily by chatbots or offshore personnel who do not possess deep industry expertise. In mission-critical industries, that approach carries risk.

Facilities in the bulk materials industries represent millions of dollars in revenue to their owners and are essential to infrastructure, construction, food production, waste management and recycling. The software that operates these facilities must be purposefully built, carefully tested and thoughtfully deployed. When problems arise, customers need knowledgeable professionals who understand both the technology and the business. Automated responses alone don’t fix the problem.

Trust Still Drives Technology Decisions

There is no question that the pace of change will accelerate in the age of AI. Software providers must innovate more rapidly. And if their customers want to remain competitive and profitable, they should adopt these innovations at a faster pace than they have in the past. Clear communication about those changes remains essential.

Sales professionals, product managers, customer success teams and implementation engineers will play a crucial role in guiding customers through modernization in a way that protects operations while delivering measurable value.

Simply put, AI is here to stay, and its transformative potential should not be underestimated. Legacy systems designed with fairly modern architectures will evolve, and development cycles will shorten. But the importance of trusted human relationships should not be underestimated.

In enterprise software, particularly in mission-critical industries, adoption does not occur at the speed of innovation alone. It occurs at the speed of trust.

Barry Honig is co-founder, CEO and president of TruckPay, a technology company that provides mobile and cloud-based logistics and scale management systems for the bulk materials industry. He has more than 40 years of experience in technology and financial services, including senior technology roles at Morgan Stanley. Honig holds seven patents related to contactless truck scale and fleet logistics systems. He earned a bachelor’s degree in applied mathematics from Columbia University’s School of Engineering and completed graduate work in computer science. He serves on the boards of directors of Lighthouse Guild International and Freedom Guide Dogs.