Over the past year, the AI world has embraced the idea of “treating AI agents like interns.” Executives from Big Tech, such as Microsoft and Salesforce, have urged companies to temper expectations and assign AI small, simple tasks, as if the technology is still earning trust. However, limiting AI to “intern” duties leads to equally […] The post Stop Treating AI Agents Like Interns: It’s Time to Demand Results appeared first on TechBullion.Over the past year, the AI world has embraced the idea of “treating AI agents like interns.” Executives from Big Tech, such as Microsoft and Salesforce, have urged companies to temper expectations and assign AI small, simple tasks, as if the technology is still earning trust. However, limiting AI to “intern” duties leads to equally […] The post Stop Treating AI Agents Like Interns: It’s Time to Demand Results appeared first on TechBullion.

Stop Treating AI Agents Like Interns: It’s Time to Demand Results

Over the past year, the AI world has embraced the idea of “treating AI agents like interns.” Executives from Big Tech, such as Microsoft and Salesforce, have urged companies to temper expectations and assign AI small, simple tasks, as if the technology is still earning trust.

However, limiting AI to “intern” duties leads to equally limited outcomes. If you treat AI as minor support, your results will reflect that level of ambition: routine, generic, and easy to replace. The real value of AI becomes most apparent when you push it beyond efficiency and cost savings, expecting stepped-up business results. Companies that ask AI to deliver on meaningful objectives unlock a true competitive advantage.

Silicon Valley’s biggest companies are already planning to pour $400 billion into AI efforts this year. While this eye-popping Big Tech investment and the branded products they offer may appeal to decision-makers, the results often lack specificity, domain expertise, and clear objectives. These platforms handle questions and automate summaries like an intern, but don’t move the needle when it comes to impact and outcomes.

As a specialized provider focused on sports, entertainment, and tourism, we look at AI agents as experienced coworkers who should perform as revenue-driving specialists with clear objectives. The right configuration makes them more than virtual helpers. They act as collaborators, each focused on a key result, tracked by business units that matter to senior leadership.

Consider what occurs at a sports stadium. The usher can direct you to the concession stand,  but most cannot draw you a map, or optimize your route through the retail store or upsell you on premium items. You would not rely on a new intern to redesign an entire fan journey or maximize stadium sales. Setting the bar low for your technology does your business no favors.

Our approach is to build AI agents around clear OKRs,(objectives and key results). We know chatbots can answer FAQs, but can they be more than just respond? 

Instead of asking “Where can we plug in AI?”, we ask our clients: 

The answers to that question become the key results that define what each AI agent should accomplish. We develop expert agents with specific goals. One that optimizes parking, another that drives food and beverage sales, and another that handles ticket purchasing and suite sales. Each agent’s performance and contribution can be mapped directly to the metrics leaders care about. When agents collaborate, they offer a coordinated, seamless, and personalized experience for each fan. For example, a guest experience agent assists with arrival, a food and beverage  agent provides timely offers, and a ticketing agent ensures purchases convert quickly. This teamwork leads to better customer experiences, greater revenue, and higher OKRs.

An OKR-focused model also changes the conversation inside organizations. This approach clarifies ownership. Each agent aligns with the business leader who cares most about its function. Ticketing reports to revenue,  food and beverage to concessions, guest experience to marketing and operations. Rather than leaving AI decisions to junior contacts, defining objectives from the start engages senior leaders and executives. It now becomes a C-suite-level initiative that can be measured, adjusted, and forecast. As domain experts who can deliver measurable impacts, smaller, specialized technology companies can outcompete larger vendors by demonstrating business results, not just spending power.

Much of today’s AI narrative emphasizes efficiency and automation. Leaders should look past that. The question is not how many repetitive tasks an agent can handle. The real question is, what does this AI actually accomplish for the business?

If you only want convenience, set expectations low. To unlock true value, assign AI a domain, give it a clear goal, and expect results worthy of an experienced business partner. Organizations that follow this approach will lead the next phase of digital transformation.

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Donny White is the CEO and co-founder of Satisfi Labs, an Agentic AI platform powering customer engagement for some of the world’s leading sports, entertainment, and tourism brands.

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