Beyond vision and roadmaps, a CPO’s fundamental role is to act as a steward of the company's R&D investment. The primary measure of success is the ability to ensure that every dollar spent on development translates into tangible, measurable enterprise value for the business.

Intangibles can be systematically analyzed by categorizing them into four key pillars: intellectual property, brand equity, human capital, and network effects. This framework helps investors move beyond traditional accounting metrics to assess a company's true value.

The debate over AI chip depreciation highlights a flaw in traditional accounting. GAAP was designed for physical assets with predictable lifecycles, not for digital infrastructure like GPUs whose value creation is dynamic. This mismatch leads to accusations of financial manipulation where firms are simply following outdated rules.

To overcome accounting's focus on historical costs, quantitative investors use unstructured data from sources like patent filings, trademarks, and LinkedIn profiles. This approach quantifies the actual output and quality of a company's intellectual property and human capital.

Some tech companies have doubled the depreciable life of their AI hardware (e.g., from 3 to 6 years) for accounting purposes. This inflates reported earnings, but it contradicts the economic reality that rapid innovation is shortening the chips' actual useful life, creating a significant red flag for earnings quality.

Traditional valuation multiples are increasingly misleading because GAAP rules expense intangible investments (R&D, brand building) rather than capitalizing them. For a company like Microsoft, properly capitalizing these investments can drop its P/E ratio from 35 to 30, revealing a more attractive valuation.

The CEO of Judges Scientific uses Return on Total Invested Capital (ROTIC) instead of the more common ROCE. He argues ROCE is an "accounting fiction" because amortization shrinks the capital base over time, artificially inflating returns. ROTIC provides a more honest measure based on the actual capital invested.

Current AI spending appears bubble-like, but it's not propping up unprofitable operations. Inference is already profitable. The immense cash burn is a deliberate, forward-looking investment in developing future, more powerful models, not a sign of a failing business model. This re-frames the financial risk.

Companies investing heavily in intangibles like R&D often see a temporary drop in earnings per share (EPS). This spending, however, builds long-term competitive advantages and moats, leading to substantial EPS growth over a multi-year horizon.