How should investors value AI companies when most are not yet profitable at scale?

Valuing AI companies that are not yet profitable at scale is challenging because traditional capital markets, built for linear growth, struggle with AI's exponential paradigm and high capital expenditures, leading to market volatility and doubts about returns [1][7]. Investors should consider the investment opportunities approach, which justifies high, bubble-like valuations by focusing on future growth potential rather than current earnings, as AI represents a general-purpose technology with uncertain competition and long-term value creation [3][9]. However, this requires emphasizing scalable returns, monetization strategies, and governance to mitigate risks like over-investment and potential bubbles, where profits may only cover half the needed investment [6][11]. Sources do not provide detailed valuation formulas but highlight shifting from short-term profits to extended ROI horizons amid fundraising tactics that inflate perceived worth [2][4].