The Fight Will Be Putting AI Inside Operations

Intelligence that does not enter the workflow is expensive ornament.

After the initial shock of generative AI, every company will try to look modern. There will be presentations, committees, pilots, announcements, partnerships, internal labs, executive posts, and empty phrases about transformation. This is inevitable. The first corporate reaction to a powerful technology is aesthetic. The company wants to look awake before it truly changes.

But the next contest will not be who "has AI." That phrase will become cheap. The contest will be who can put AI inside operations without breaking governance, margin, compliance, security, and responsibility. Palantir appears as the obvious name because it speaks exactly this language: data, operations, decision, permission, model, workflow. But ServiceNow, MongoDB, Snowflake, and Datadog can capture relevant parts of the same shift.

ServiceNow lives in workflows. If AI needs to trigger processes, open tickets, prioritize tasks, automate internal support, reduce administrative work, and connect departments, workflow platforms gain importance. The model alone talks. The workflow does. The company pays more for doing than for talking.

MongoDB represents the application and flexible data layer. As companies build AI applications, they need databases, storage, search, structure, and flexibility to handle data that does not fit well in old systems. Snowflake represents corporate data, governance, sharing, analytics, and the attempt to be the layer where the company organizes information for smarter use. Datadog represents observability. Systems with AI break, cost money, degrade, make mistakes, and need monitoring. What is not observed becomes risk.

Palantir may capture the strongest narrative because it sells the idea of connecting AI to real decisions. But the corporate market will not be won by one company alone. Each layer will try to say: "AI needs me to be useful." And many will be partially right.

Perhaps in 2024 the market begins to separate companies that merely say AI from companies that have structural right to capture AI budget. That right comes from being close to data, process, developer, infrastructure, or decision. The company that merely adds AI as a cosmetic feature may receive temporary attention. The company that embeds AI in a critical flow may receive real expansion.

The reader's profit will be in asking: where does AI become routine? Not demo. Routine. What enters routine enters recurring budget. What remains in the demo enters the memory of the annual event and then dies.

Palantir needs to prove that AIP is not just theater for investors. It needs to show deployment, usage, expansion, commercial customers, operational impact. ServiceNow needs to turn automation into higher value per customer. MongoDB needs to show developers choosing its infrastructure for modern applications. Snowflake needs to defend its position against hyperscalers and open formats. Datadog needs to remain an indispensable visibility layer in more complex environments.

The counter-thesis is that enterprise AI can become an embedded feature, not a separate product. Margins can be pressured by model costs. Customers can resist paying extra. Corporate data can be too bad. Integration can be slow. Security can block usage. Regulators can demand controls. Palantir can be controversial. Snowflake can face intense competition. MongoDB can be expensive. Datadog can suffer from spend optimization. ServiceNow can have a demanding multiple.

But the thesis remains: the corporate value of AI will be measured by operational change, not enchantment. A company does not improve because an employee can ask for a pretty summary. It improves when the sales cycle shortens, fraud falls, support resolves faster, inventory improves, collections prioritize better, maintenance anticipates failure, legal triages documents, engineering reduces incidents, and management decides with less delay.

Real AI disappears inside the process.

When it becomes routine, the market calls it productivity.

Leo Bentier