Scaling GenAI With Confidence: Anna E. Molosky’s Blueprint for Real ROI

Across my work with global organizations, I see the same pattern repeat itself.The problem with GenAI adoption isn’t ambition — it’s sequence.

Too many companies rush into futuristic, high-visibility GenAI initiatives before stabilizing the foundational workflows that actually move financial metrics. When that happens, AI looks impressive — but fails to show up on the balance sheet.

Here’s a grounded reset on how enterprises can turn GenAI investment into measurable, repeatable impact.

1️⃣ ROI Doesn’t Begin at the Front Door — It Begins in the Back Office

Most executive teams launch AI programs where visibility is highest: digital experiences, sales enablement, customer engagement. But visibility does not equal value.

The most reliable and defensible ROI consistently comes from operational fundamentals, including:

• Finance close and reporting cycles

• HR transactions and case management

• Procurement and sourcing workflows

• Shared services operations

• Reconciliation, validation, and compliance routines

These processes aren’t flashy — they’re profitable.

A clear example is AT&T. By prioritizing process-level automation over headline-grabbing GenAI pilots, the company eliminated 16.9 million manual minutes per year, achieved 20x ROI, and unlocked hundreds of millions in recurring value.

My perspective:If your AI strategy doesn’t start with the back office, it won’t scale sustainably — or deliver predictable returns.

2️⃣ Your Employees Are Already Designing Your AI Strategy — Quietly

Most organizations still approach AI roadmapping as a top-down exercise. The flaw? It ignores the thousands of bottom-up experiments already happening across the workforce.

The data is remarkably consistent:

• 90% of employees use personal AI tools to accelerate their work

• Only 40% of organizations provide sanctioned, governed access

This so-called “shadow AI” isn’t a liability. It’s intelligence.

Employees are already signaling:

• Which tasks consume the most time

• Which workflows are repetitive

• Where automation removes friction

• Which processes AI genuinely improves

Rather than guessing where value exists, leaders should observe, capture, and formalize these behaviors. Your workforce has already validated many of your highest-ROI use cases — the opportunity is to scale them securely and intentionally.

3️⃣ Enterprise AI Wins Are Measured in Years — Not Quarters

One of the most damaging misconceptions in GenAI strategy is the expectation of six-month ROI.

That timeline is incompatible with enterprise reality.

Large-scale AI transformation typically unfolds over one to three years, shaped by:

• Complex systems integration

• Data readiness and remediation

• Process redesign and standardization

• Governance, compliance, and risk frameworks

• Global workforce training and adoption

Short evaluation windows misinterpret “early-stage” as “underperforming.”

The widely cited 95% AI failure rate is less an indictment of AI and more a reflection of organizational maturity. The 5% seeing returns today aren’t fundamentally better — they simply sequenced investment correctly and set realistic timelines.

The Blueprint for Scaling GenAI With Confidence

Enterprises that generate real ROI from GenAI do three things differently:

🔹 Start with back-office, high-certainty automation🔹 Use employee-driven AI behavior to identify proven value🔹 Align expectations with the true complexity of enterprise transformation

Get the sequence right, and GenAI stops being an experiment.

It becomes a durable engine for operational efficiency, financial performance, and long-term competitive advantage.