AI Is Useful. Now What?

AI implementation is critical for every business right now, as the window for merely "sidecaring" with AI is closing. While many individuals are comfortable using AI for personal queries, its business application still presents a challenge. Businesses and their teams generally fall into one of three phases regarding AI adoption: sidecaring, AI-first, or AI-native. Most businesses are currently in the "sidecaring" phase, where AI is used on the side to inform work, much like an advanced search engine. This involves using large language models (LLMs) to generate content, edit emails, or answer strategic questions, with the output then manually integrated into core work. However, this phase is rapidly becoming insufficient. Experts like Mark Cuban emphasize that every business needs an AI implementation immediately, advocating for a shift beyond basic sidecaring. The next phase is "AI-first," which involves integrating AI directly into business workflows and systems. This means AI executes tasks, informed by real-time or just-in-time business data. Instead of a team member assuring a founder they are using AI, in an AI-first system, the AI itself can report on its usage and impact. This shift represents a significant opportunity, particularly for service businesses and internet entrepreneurs, as it fundamentally changes how information is organized, traded, and assembled. It moves beyond personal piping, where an individual might train an AI, to business-level piping, where historical data is integrated to inform future actions across the entire company. The "AI-native" phase is the most advanced, where the business operates almost entirely via AI, with human intervention potentially limited to core financial harvesting. In this phase, AI agents could even sell to other AI agents. This presents both immense opportunities for efficiency and significant challenges, particularly regarding security, as agents operating at massive scales could introduce new vulnerabilities. The long-term implication is a re-evaluation of human utility in many online roles, as AI could automate a significant portion of current work. The transition to AI-first involves re-architecting business processes. One highly effective application is real-time "dashboards" or "scoreboards." By piping in business data, AI can generate immediate, customized reports on key metrics like sales calls, new customers, and revenue. This provides continuous motivation and accountability, accelerating business growth by offering real-time insights that previously took significant time and effort to compile. This allows for daily or even hourly monitoring of processes like customer onboarding, enabling swift adjustments and improvements. Another crucial AI-first application is in CRM and campaign construction. Traditional CRM systems, while valuable for managing data relationships, often require users to conform to a generalized interface. With AI, businesses can move beyond this, directly querying data to segment customers and construct highly targeted campaigns. Instead of adapting data to a pre-designed system, AI allows for a more direct, strategic approach to customer outreach and engagement, based on specific business needs and data relationships. This capability eliminates the need for extensive training on complex interfaces and enables immediate access to specific customer insights for tailored actions. Financial intelligence is a third powerful application. Many entrepreneurs, despite their creativity and passion for building products, often lack deep financial knowledge. AI can democratize access to sophisticated financial analysis. By exporting data from accounting software, businesses can gain immediate insights into their valuation, customer acquisition cost (CAC) ratios, profitability of product lines, pricing leverage, and cash flow cycles. This allows founders to identify and address fundamental flaws in their business models early, preventing potential long-term issues that might otherwise go unnoticed until it's too late. Building landing pages and running content experiments are also being revolutionized. AI empowers non-technical individuals to quickly design and deploy landing pages, accelerating growth and revenue experiments that previously required significant time and resources from design agencies or web developers. Similarly, AI can formulate and inform content experiments, both paid and organic, by leveraging historical and competitor data. This allows businesses to rapidly test content theses, analyze market trends, and generate marketing materials directly from customer interactions, such as sales calls, ensuring that the language used resonates with the target audience. The shift to an AI-first approach changes the dynamic of work, reducing the time spent on "setting the table" (data gathering and preparation) from 80% to 20%, and increasing execution time from 20% to 80%. This makes work more engaging for team members, as they can focus on higher-value tasks. AI-first strategies are also being applied to communication and lifecycle marketing workflows. Many bootstrappers neglect comprehensive lifecycle marketing due to time constraints, focusing only on current and prospective customers. AI enables businesses to quickly set up and modify onboarding sequences, nurture campaigns, and sales workflows. By analyzing recorded calls and customer interactions, AI can generate marketing materials, case studies, and even identify common terms used by customers, integrating these insights directly into sales copy and communication strategies. This allows businesses to bake best practices into their workflows more rapidly, accelerating value delivery to clientele. Ultimately, the core question for entrepreneurs is how to leverage AI to enhance existing business models and remain valuable. The answer lies in embracing the entrepreneurial spirit that built the business, but now with a powerful new toolkit. This involves re-evaluating and rebuilding workflows with AI at the core, transforming processes that are fundamental to how businesses operate and make money.