AI Predicts Tough '25 for Restaurants

Tasked Top AI Models to Analyze Industry Data - The Results are Not Optimistic

Over the past several weeks I’ve been deep in pushing the boundaries of what practical information I can get from top AI models with minimal hallucinations. I took 3 of the top ‘reasoning’ models and set them loose on our restaurant industry knowledge base, historical data, and current economic factors to identify potential risks and vulnerabilities in different restaurant segments. The results provide fascinating insights into both, how the models returned cogent results - but also raised a lot of flags about how today's economic conditions might impact the industry in ways that differ from previous downturns. This analysis stands in stark contrast to most industry projections currently circulating, which focus on "easy comp" sales comparisons versus last year that also emphasize outstanding results from a handful of over-performers. While industry headlines celebrate these success stories, the strong performance of larger chains can create biases in industry indexes that primarily track public company performance, potentially masking broader warning signs in the underlying economic data.

The January PCE Numbers Raise Concerns

The recently released January PCE report shows a complex economic picture: inflation cooled slightly to 2.5% (down from 2.6% in December), but consumer spending plummeted across both goods and services. Retail sales fell 0.9% in January—the largest monthly decline in a year. Meanwhile, the Conference Board's consumer confidence index plummeted from 105.3 to 98.3 in February, the largest drop since August 2021.

These indicators suggest consumers are pulling back significantly, which traditionally hits restaurants hard. However, the AI analysis suggests the impact may be distributed differently than in previous downturns.

A Post-COVID Industry Has Different Vulnerabilities

When I first asked for an analysis based purely on historical patterns, the AI predicted severe impacts across all segments, with fine dining facing traffic declines of 10-15% and even QSR seeing 2-5% drops. But when I provided additional context about how COVID had already reshaped the industry, the projections shifted dramatically.

According to the National Restaurant Association's 2025 State of the Industry Report, the restaurant segment mix has shifted substantially since 2019, with Fast Casual and QSR gaining 5-6 percentage points in market share.

This structural shift in the restaurant landscape has significant implications for how different segments may respond to economic pressures. As shown in the charts above, Fine Dining and Casual Dining have lost market share while Fast Casual and QSR have gained ground. This reconfiguration means traditional vulnerability patterns may no longer apply.

The Food Inflation Gap Shifts Competitive Dynamics

My analysis requires significant revision when considering the persistent gap between food-away-from-home and food-at-home inflation. According to the Bureau of Labor Statistics, restaurant prices (food away from home) have consistently outpaced grocery inflation (food at home) for the past 18 months. This fundamentally alters traditional segment vulnerability patterns:

1. QSR's Position Weakens: Historically the most resilient segment, QSR now faces increased vulnerability due to:

   • More aggressive price increases (7-8% annually over the past 2 years) than other segments

   • Eroded value perception as dollar menus have largely disappeared

   • Greater susceptibility to grocery trade-out as the price gap widens

   • Less differentiated experience to justify the premium over eating at home

2. Fast Casual Benefits From Relative Value: Fast casual chains have implemented more moderate price increases (5-6% annually), improving their relative value position:

   • The price gap between QSR and fast casual has narrowed

   • Quality perception remains stronger

   • Digital infrastructure enables better targeted promotions

   • Portion sizes often offer better value perception

3. Casual Dining Shows Unexpected Resilience: With more moderate recent price increases (4-5% annually), casual dining's value proposition has improved relative to QSR:

   • Experience factor helps justify the premium

   • "Affordable indulgence" positioning becomes more attractive

   • Greater ability to offer targeted promotional pricing

The QSR Discount Wild Card

A critical factor that could dramatically alter these projections is the potential for QSR chains to aggressively return to deep discounting. There are already early signs of this shift with several major chains introducing $5 meal deals and app-exclusive promotions. If this trend accelerates, it could:

1. Shift Value Perception Back to Pre-Inflation Era: Compelling value offerings could restore QSR's traditional position as the value leader

2. Recapture Grocery Trade-Out Traffic: Deep discounts could overcome the grocery price advantage, particularly for convenience-oriented occasions

3. Come at Significant Cost to Near-Term Profitability: Most QSR operators have seen commodity and labor costs increase 25-30% since 2019, making these discounts potentially margin-destructive

4. Create Segment-Wide Pressure: Once major chains initiate aggressive discounting, competitive dynamics will likely force others to follow

5. Benefit Larger Chains with Scale Advantages: Smaller QSR operators may struggle to maintain margins while matching promotional pricing

This potential strategy shift creates a binary outcome possibility for QSR—either continued traffic erosion if they maintain current pricing strategies, or potential traffic growth but with severe margin compression if they aggressively discount. The net effect on the segment could be a zero-sum game where traffic improves but profitability suffers dramatically.

The COVID "Survivor Bias" Effect

A compelling insight from this analysis is how the 20% closure rate during COVID—which disproportionately affected full-service restaurants—creates a significant "survivor bias" that alters traditional vulnerability patterns.

Importantly, not all survivors were created equal. We're now seeing two distinct categories of COVID-era survivors:

1. The True Adaptors: These operators fundamentally transformed their business models—developing robust off-premise channels, restructuring labor models, renegotiating leases, and implementing menu engineering to combat inflation. These businesses emerged stronger and more resilient.

2. The Capital Floaters: These operators merely tapped into the unprecedented low-interest liquidity available during COVID without implementing meaningful operational changes. They survived the initial crisis through financial engineering rather than business model adaptation.

The restaurant bankruptcies we saw throughout 2024 were largely driven by this second category—businesses that floated on cheap capital but failed to evolve. What's concerning is that not all these "zombie companies" have yet been flushed out of the system. As economic headwinds intensify, we're likely to see additional closures among operators who survived the pandemic but failed to adapt to the post-pandemic reality.

This distinction is crucial for understanding segment resilience. The true measure of a segment's vulnerability isn't merely who survived COVID, but how they survived and whether they made the fundamental changes necessary for long-term viability in today's economic environment.

Industry Structure Has Fundamentally Evolved

The 5-6 point shift toward Fast Casual and QSR over the past six years has created a new market equilibrium. There's now reduced competitive density in full-service segments and the market has already adjusted to lower full-service demand.

This structural shift means that remaining full-service restaurants face less competition for a smaller but more dedicated customer base. Meanwhile, the expanded fast casual segment faces increased internal competition that may amplify the impact of any consumer pullback.

Multiple Signals Beyond January's Numbers

The AI analysis flagged several concerning signals beyond just January's performance:

1. The dramatic consumer confidence collapse reflects deeper economic anxiety

2. Job growth concentrated in lower-wage public sector positions limits spending power—a concern that will be amplified by the impending federal job cuts announced by the Trump administration

3. Upcoming tariffs create additional uncertainty, especially relevant for food costs

4. Persistent high interest rates continue to constrain discretionary spending

The impending federal job cuts pose a particular risk for restaurant traffic in regions with high concentrations of government employment. These cuts will not only directly impact those employees but also create ripple effects throughout regional economies dependent on government spending, potentially worsening consumer pullback beyond what January's numbers suggest.

Strategic Implications for Operators

For those of us in the restaurant industry, this revised analysis suggests several strategic imperatives:

Fine Dining: Focus on exclusivity and experience value rather than discounting. Emphasize what makes the experience irreplaceable.

Casual Dining: Leverage improved relative value position. Emphasize portion size and shareable options that highlight total value beyond just price.

Fast Casual: Double down on quality-to-price messaging. Menu engineering should emphasize items where value perception is strongest compared to QSR alternatives.

QSR: Face a strategic inflection point—either embrace aggressive discounting to drive traffic at the expense of margins, or focus on product quality improvements to justify premium pricing. The middle ground may prove increasingly untenable.

Conclusion: The Power of AI-Driven Scenario Analysis

It's important to emphasize that the projections examined here are AI-generated, and the jury is still out on whether these models will prove more or less reliable than traditional human analysts. Biases exist in both approaches—AI models are limited by their training data and underlying assumptions, while human analysts often bring their own experiential and cognitive biases to their forecasts.

The real potential power in this approach isn't about whether AI or humans are "right," but rather how much easier it is now to harness data and applied mathematics for rapid scenario simulation. At a time when uncertainty has become a new constant in our industry, simulation analysis provides an effective tool for ensuring businesses can quickly navigate change.

This type of scenario analysis using AI is fundamentally part of what Decision Intelligence (DI) is all about. Signalflare.ai's advanced DI approach sits at the cutting edge of this revolution, combining massive data ingestion capabilities with advanced machine learning to enable restaurant leaders to make better, faster decisions amid complexity and change.

By running multiple scenarios with different assumptions, restaurant operators can:

• Identify previously hidden vulnerabilities in their business models

• Prepare contingency plans for various economic outcomes

• Recognize early warning signals that indicate which scenario is unfolding

• Adjust strategies more quickly as conditions evolve

What's clear from this exercise is that generic "recession playbooks" may not apply in our post-COVID industry structure with its unique inflation dynamics. The most successful operators will use data-driven approaches to continually monitor spending patterns and relative price positioning within their specific customer segments.

I'll continue exploring how these new analytical tools can help restaurant leaders navigate economic uncertainty with greater confidence and agility. The January spending pullback is concerning, but with the right scenario planning, operators can prepare for multiple futures rather than betting on a single outcome.

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