Resilience scoring that pierces through AI mumbo jumbo

With ChatGPT’s explosive growth and the promise of transformative AI applications, investors are caught in a whirlwind of FOMO-driven decisions, inflated valuations, and grandiose expectations. Every AI startup pitch seems to promise revolutionary disruption, leading to increasingly irrational investment patterns that mirror the dot-com bubble’s euphoric excess.

Some investors are making rapid-fire decisions based on buzzwords like “machine learning,” “neural networks,” and “generative AI” without conducting thorough due diligence. Valuations have skyrocketed for companies with minimal revenue but impressive AI-laced product demos. Too many new accelerators have also pitched tent to coach startups on how to get funded, condoning the frantic chase for every AI trend, from autonomous vehicles to AI-powered content creation, often without understanding the underlying technology or market dynamics.

However, while investors appear hypermanic, the ones SMEMojo has worked and spoken with openly admit that gauging AI appropriateness in a startup’s strategy has been difficult, and is where they need help the most. Their confidence in their decision on the other levers of their evaluation repertoire is what enables them to still act, but that’s not sustainable given AI’s rapid takeover.

Another thing that we found in investors who are used to using growth metrics (rather than risk) is that they posit too much in the score as to what all good things it can predict. Again, myopically growth-minded. Some have even asked us if the RIC Score predicts valuation and exit price, and thought only then would such a score be helpful. Of course, we were quick to point out that “resilience” is just the opposite of “failure” - both are on the same spectrum, a risk metric. It does not matter how high the valuation or exit price is if the startup/SME has a very low resilience score. That is, the RIC Score is a lens on top of what investors are used to evaluating, as not all high valuation startups (according to their own models) are worth their investment.

SMEMojo’s Resilience and Investability Certification (RIC) Scoring offers a systematic due diligence framework that includes scrutiny of the startup’s data and architecture to measure their “AI forwardness”. We further map that into a matrix of the startup’s culture, strategy and scalability. The way we assess the startup is also unique and nonfungible, unearthing ~200 factors to corroborate the startup’s self-reported information. So, it’s not just looking at financial health, market opportunity, competitive positioning, team capability, technology differentiation, scalability potential, and risk factors individually; it’s an elaborate knowledge graph or context that ultimately indexes the startup on their resilience, with growth and risk levers intermeshed.

Breaking the Cycle of Irrational Exuberance

The beauty of structured scoring systems like the RIC Score lies in their ability to ground abstract excitement in concrete metrics. Instead of getting caught up in grandiose visions of AI transforming entire industries, investors must confront specific questions: What is the startup’s current burn rate? How defensible is their technology moat? What evidence exists of product-market fit? How realistic are their scaling projections?

Most importantly, certification scores provide objective benchmarks that cut through the hype surrounding AI startups. When every company claims to be using “revolutionary AI technology,” a structured and in depth evaluation framework helps investors distinguish between genuine innovation and clever marketing. It separates startups with solid technical foundations from those riding the AI wave with superficial applications of existing technologies.

These scores also help investors maintain portfolio balance by highlighting when they’re becoming overexposed to specific AI niches or risk profiles. The systematic nature of the evaluation process makes patterns visible that might otherwise be obscured by the excitement of individual deals.

Structured certification processes also create valuable documentation that serves as a reality check over time. When market conditions inevitably shift and the AI bubble shows signs of deflating, investors can review their scoring rationale to understand what factors drove their decisions. This historical perspective becomes invaluable for refining future investment strategies and avoiding repeated mistakes.

Embracing Rational Optimism

By implementing systematic scoring approaches, AI startup investors can cure their hypermanic symptoms without losing their edge or reputation. They can still identify and capitalize on genuinely revolutionary opportunities while avoiding the pitfalls of euphoric decision-making that have historically plagued emerging technology sectors.

The prescription is clear: structure, patience, and systematic evaluation. The cure for AI investment mania isn’t pessimism—it’s disciplined analysis.