The greatest value of AI is that it fosters a culture of performance. If the primary value of innovative technology is efficiency, automation, and knowledge delivery, then the performance of all operational functions must improve accordingly. But the reality is that the huge ROI promised to businesses is not being realized at scale.
According to Nvidia CEO Jensen Huang, $3 trillion to $4 trillion will be spent on AI infrastructure by the end of the decade. When technology hyperscalers deploy that kind of capital, they want CEOs to buy into their technology vision. fast:
“If you ignore AI, you risk becoming irrelevant. Deploy AI, and deploy it fast.” – Eric Schmidt, former CEO of Google
“The pace of advancement in artificial intelligence…is growing at an almost exponential pace.” — Elon Musk
“If you don't have an AI strategy, you're going to die in the coming world.” — Devin Wenig, Business Insider
This combination of urgency, passion, and resoluteness has led companies to make major investments in AI.—There is little focus and little understanding of what the real impact will be. Big bets without a strategy have not been proven to create meaningful shareholder value.
Economic historians point to clear lessons from the early days of electrification. When factories replaced steam engines with electric motors, the results did not have the impact that most expected. The main reason is that in the rush to adopt innovation, we retained traditional floor plans optimized for mechanical power. It took decades for companies to realize meaningful profits. Lesson learned: Innovative technologies are rarely best suited to traditional workflows and infrastructure. “Going all in on AI” makes a great headline and allays the concerns of fearful board members—But is it actually the best way to start transforming your company and evolving your business?
This is where microdosing comes into play.
It was made famous by Dr. James Fadiman's 2011 book. Psychedelic Explorer's Guidemicrodosing LSD and hallucinogenic mushrooms have become firmly entrenched in Silicon Valley's “biohacking” community. Engineers, executives, and creative people have adopted microdosing not to “tune in and drop out” but to increase creativity, improve coding, and expand mental capabilities. They sought to realize the benefits of activating new features while minimizing the risks of full-scale use. Think of it this way, microdosing may offer a more strategic avenue for AI.
Almost every global company operates within a complex technology ecosystem, or “stack,” dominated by one large software company. Salesforce, Microsoft, Oracle, SAP, and ServiceNow have vast footprints and often coexist with cloud infrastructure providers such as Amazon Web Services, Google Cloud, Microsoft Azure, and Alibaba. Each has invested billions of dollars in AI platforms, agents, security tools, and data management. They are urging CEOs to bet big on a vision of an AI-dominated future. But there is a problem lurking in this room that is too often overlooked. Few companies have the executives and staff with the experience needed to manage disruptive, transformative, and frankly dangerous technology.
Large organizations don't need to serve as proof-of-concepts or test cases for technology vendors. Instead, “AI microsolutions”—AI version of microdosing—provides a much more manageable and attractive option. Now, many of you may be thinking, “I've already invested in a pilot or proof of concept,” but that's not the same as a microsolution. We are not creating AI orphans that will be abandoned after a period of testing and ROI analysis. Rather, microsolutions solve real-world problems and create impact that grows over time.
With this background in mind, here are five microdosing methods to get you started that any company can implement within a manageable time frame.
First Dose |Sales Team Intelligence
One of the opportunities presented by AI is the codification and systemization of revenue supply chains that integrate product, marketing, and sales. Sales teams are the natural starting point for that long-term transformation. Accelerate your revenue generation by knowing what your customers really want and getting and reacting to feedback quickly. Who has the best access to that information? The sales team. Collecting sales intelligence is one of the easiest AI solutions to implement. With conferencing tools like Google, Zoom, and Fireflies, and sales listening tools from Gong, Chorus.ai, and Clari, organizations can gain robust, real-time customer intelligence from every interaction. This requires little disruption to the existing technology ecosystem and provides valuable insights for sales, marketing, and product teams. Starting with your sales team creates a powerful cultural catalyst for the rest of your organization.
Second dose | Reconsider—even reconsider—external service provider
Learning and experimenting with key partners is a great place to start. For publicly traded and PE-owned companies that spend large amounts of money on external auditors and external law firms, AI presents an immediate opportunity to reduce costs. AI works best when there is reliable data to refer to, and when legal contracts have the structure, rules, and workflows that enable robust functionality. In addition, external auditors can create conversational audio and visual dashboards (think briefings and reports) that allow executives to interact verbally and display them visually on demand. In-house teams can analyze specific clauses and potential changes to contracts without direct human intervention. Key decision makers will still need to scrutinize important decisions, but these functions are ripe for rapid and meaningful advancement. Investing in these external services should result in significant cost savings over time.
Third dose | Enhanced customer experience
Nothing bothers customers more than feeling undervalued and unknown. Many organizations, such as financial services companies, mobile carriers, insurance companies, broadband providers, and healthcare organizations, have years of data that their customers want to remember and consider in their interactions. AI is the ultimate tool to improve customer experience in these environments. Equip every customer-facing team member and system with context. Most of us have experienced the power of Spotify's personalized playlists, Netflix's movie recommendations, or American Express's location-based restaurant suggestions. When customers feel seen and heard, their impression of your brand increases significantly. This is a capability that ecosystem partners like Salesforce, ServiceNow, and Oracle can activate quickly and at scale with minimal risk.
4th dose | Get the visual
One of the most exciting advances in AI is the ability to analyze medical images alongside doctors. Research shows that this collaboration holds great promise in terms of improving diagnostic accuracy, which enhances detection while reducing unnecessary follow-up and procedures. Apply visual analytics to your business. Insurers can initiate and review car accident claims in real-time from the scene of the accident via a mobile application. Human resources departments at companies with incentivized return-to-work policies can instantly measure attendance compliance and employee interactions, and repair organizations can get feedback on complex scenarios by sharing real-time visuals. Visual data consumption is so important that Meta, Google, Samsung, and Snap have all released solutions for the consumer space.
Fifth dose | Can anyone become a decent writer? Just approx.
It's important to understand that AI's most powerful acronym, LLM, stands for Large Language Model. Language is a core strength of AI and is extremely useful across the enterprise. First, your employees will never have an excuse to write a bad email again. All major email tools now have AI-based editors that can clean up the messy narrative from your stream of consciousness over your 2am coffee. Second, creative briefs, conceptual explanations, strategy papers, and business cases can be enhanced, explored, and leveled up with leading LLMs such as Google Gemini, ChatGPT, Claude, and Microsoft Copilot. Finally, in-house teams writing social media posts, press releases, website copy, and ad copy can take advantage of a variety of low-cost, easy-to-use AI tools. Not everyone can become a great storyteller, but your language-based communication should improve overall.
The core philosophy of microdosing is to use small, consistent doses to achieve long-term effects without interfering with normal function. This is also the core of AI microsolutions. Create impact by making small, iterative improvements to core business functions without disrupting the entire ecosystem of existing systems, workflows, and data models. Organizations can continuously deploy innovation and automation to create long-term value. As AI continues to become smarter, more interactive, and more adaptive, these solutions should naturally evolve as the larger technology ecosystem implements agent AI at scale.
On the other hand, these systems require basic diligence and governance to limit risk. Consider the following:
- Customer data and privacy laws continue to apply and must be carefully managed.
- Executives and managers need to create a culture of innovation that encourages teams to embrace human collaboration with technology and AI.
- When working with partners and service providers, a clearly defined service level agreement (SLA) can help you properly distribute responsibilities.
- To avoid paying for duplicate functionality from competing vendors, you need to create a long-term interoperability roadmap with ecosystem partners.
Microdosing has created a methodology to reframe the huge risks of LSD and psychedelic drug abuse and bring their use into the mainstream. Microsolutions have the same potential for enterprise organizations. This enables businesses to deploy innovative technologies at a manageable scale, allowing teams to scale their effectiveness and better prepare for the transformative impact AI will have on the global economy.
