Persistent Inflation & Rising Operating Costs
Why Boards Are Still Worried and When They Can Stop
Inflation has eased from the emergency levels seen in past years, but for boards of directors and advisory boards, the lingering pressure on operating costs remains one of the most persistent strategic concerns. For many organizations, inflation is no longer a headline—it’s an everyday operational reality. Although national inflation numbers may appear stable, the underlying categories that matter most to businesses—labor, transportation, logistics, and services—continue to rise at uneven and unpredictable rates. Boards worry because even small cost upticks compound into margin compression, which in turn hits investor confidence, valuation, and cash flow.
One of the biggest drivers of concern is wage inflation, which has not softened nearly as much as other categories. Skilled workers in areas such as technology (especially AI), cybersecurity, supply chain, and professional servicechats continue to command premium salaries. Operating teams struggle to balance competitive compensation with financial discipline. Boards understand that underpaying risks losing key personnel, but overpaying can quickly inflate budgets beyond what revenue growth can support. This tension makes labor costs uniquely difficult to manage.
Here are some representative salary ranges for AI / ML / Data Science roles in U.S.-based financial services (or similar) based on recent data. AI experts’ salaries in Financial Services have increased between 25-30% over the last two years:
- Financial Data Scientist
- According to Salary.com, a financial data scientist earns a median base salary of about $129,606/year, with a typical range from ~$118,700 to ~$139,600.
- On 6Figr, reports suggest total compensation (base + bonus etc.) can average around $133K, but some profiles indicate much higher pay depending on experience / role.
- AI Data Scientist
- According to Salary.com, an “AI Data Scientist” with 8+ years of experience might average around $140,585/year in base pay.
- AI / ML Engineer
- In New York City, an AI Engineer’s base salary averages $223,464 per Built In data, with total compensation typically around $242,000.
- Indeed reports for “AI/ML Engineer” in New York, NY: average ~$165,231 for base salary, though postings vary widely (from ~$107K to $255K) depending on level.
- For New York State more broadly, average is ~$157,426 for AI/ML engineers per Indeed.
- Senior / Lead AI Engineer in Financial Services
- According to job-post data on Reddit (so take with a grain of salt), a Lead AI Engineer role at Capital One in New York is advertised at $211K–$240K, plus performance incentives.
- A Senior Lead AI Engineer at Capital One on Reddit is advertised at $245K–$280K + incentives.
- For a Senior AI Engineer role at Goldman Sachs, a Reddit post shows a broad compensation range of $150K–$300K, which presumably reflects very different levels / experience.
- Very High-End / Hedge Funds
- In hedge funds or ultra-quant shops, the pay can go much higher. For example, Point72 reportedly offered up to $400,000 base for a staff AI/ML engineer.
Boards are also closely watching pricing power. In many industries, the ability to pass increased costs down the value chain has weakened. Consumers have become more price-sensitive, and enterprise buyers are delaying purchases, renegotiating contracts, or shifting to more cost-effective alternatives. This means companies are absorbing more of the cost pressure internally. The board’s concern is not merely today’s expense profile—it’s the long-term balance between revenue and cost structure.
Another key challenge is the unpredictability of supply-chain-related inflation. Energy costs, shipping rates, and raw material prices are still volatile. Even when supply chains appear stable, geopolitical disruptions or trade policy changes can produce sudden cost spikes. Scenario planning becomes difficult, and budgets are constantly being revised.
So when can boards stop worrying?
Boards can begin to relax when inflation shows consistent, broad-based declines over several quarters—not just in headline CPI but in core categories that directly affect business costs. If wage growth stabilizes relative to productivity, boards gain confidence that compensation structures are sustainable. Cost stability in transportation, energy, and logistics is another green light because these categories can swing margins dramatically.
Boards should also stop worrying once the organization proves it can operate efficiently at the new normal cost level. This means:
- A healthier balance between fixed and variable costs
- Clear pricing strategies that customers accept
- Strong productivity metrics
- Digital and AI tools reducing manual overhead
Finally, boards can ease their concerns when the company builds an agile cost-management discipline—one that doesn’t rely on unpredictable external factors. If the organization can protect margins despite inflation, the board’s anxiety naturally diminishes.