Beyond the Buzzwords: How to Tell if an AI Solution is Ready Today or a Roadmap Promise

Since I joined Encompass, it didn't take long to recognize what makes it distinct. This industry has generations of history behind it, where relationships and reputations are built over decades, not quarters. That context matters when you're thinking about AI. The tools you adopt should support the way your business actually works, not disrupt what's taken years to build.

Right now, you can’t attend an industry trade show or scroll on LinkedIn without being bombarded by "AI." Every company is slapping an AI label on their product and making big promises, but what that means for your operation can be confusing.

The problem is that you can’t simply wrap a legacy system in generic artificial intelligence. True innovation isn’t a bolt-on feature; it requires a completely unified architectural foundation tied directly to your core operational data.

As you evaluate the tech landscape, ask yourself these questions about your technology partners:

• Are they focused solely on just speed-to-market, or are they building at speed with a commitment to releasing real working products? Execution speed shouldn’t compromise product quality and long-term value. Doing it right means delivering real working products that help you maintain your competitive edge. If they’re rushing half-baked tools to market or taking so long you’ll be waiting until 2027 and missing out on value now, then take caution. 
• Are they building true agentic AI or a glorified chatbot? Chatbots are reactive; they just answer the questions you prompt them with. True agentic AI can execute end-to-end workflows. Make sure you know what you’re signing up for and what it can actually accomplish.
• Are they willing to give you a look under the hood? Building an AI platform starts with the architecture beneath it, and it’s only as smart as the data it sits on. If a vendor is rebranding third-party tools into their suite or not giving you access to all your data, it will break at scale. Ensure they’re working with proven partners, customizing it for beverage, and using your data in order to unleash its full power.
• Are they providing peer proofs and a community to lean on? You shouldn’t have to navigate AI alone. Ask if you can talk to other distributors who are actually using these tools in production today. A true partner provides great software, consultative best practices and change management while connecting you with a network of peers where you can share real-world learnings about how AI integrates and changes all aspects of an operation.

It’s no wonder distributors have justifiable concerns about AI. A responsible, built-for-beverage partner must solve for three things:

1. Data Security & Permissions: Unbridled AI is a massive security risk. Ensure your sensitive, private company information isn’t used to train public LLMs. Prioritize the security of your proprietary data by verifying that AI agents will be operating within a secure and encrypted environment.
2. Human-in-the-Loop: AI shouldn't be built to replace your people; it should rescue them from the administrative grind. A responsible system stages the work, whether that's a route re-optimization or an AR write-off, but still requires a human to review the "Before & After" and click approve. Humans must remain firmly in control. I know this is a major concern for wholesalers who have long supported their communities and supplied meaningful jobs. AI should empower employees, not force them out.
3. Multi-Agent Orchestration in One System: Distributors need specialized agents that act as digital coworkers, instead of another siloed tool. These agents must understand the nuances of beverage distribution and collaborate with your employees to execute complex, multi-step workflows. They must be capable of tackling unique use cases that currently require completely manual effort or rely on tribal knowledge. Generic AI can’t do that, so demand a seamlessly integrated, industry-focused toolkit.

As you navigate the noise, my advice is simple: look past multi-month roadmaps, full-rebuild promises and flashy marketing. Evaluate the foundation. Demand to see products in action, solving real use cases, not screenshots or recorded demos.

While it might be tempting to hire consultants to build your agents, consider what your business loses in the process: a shared data environment across agentic departments, the robust business context they operate within, expert solutions refined by key software partners with deep industry knowledge, and much more. A truly AI-first partner won't offer you a shortcut or an excuse. They will offer you a foundation built to last.

Over the coming weeks, expect a series of deep dives exploring the practical application of foundational AI architecture to Sales, Operations, and Accounting. If you’re heading to the NBWA Convention this fall, let’s continue the conversation there. We’ll be hosting a dedicated session with Brad Manilla from K1MS on the reality of AI in beverage distribution. We’ll get specific on real-world applications and best practices from your peers.