Large language models like ChatGPT and Claude are incredibly powerful.

But enterprise planning requires more than intelligence.

It requires trusted business context.

The challenge of using generic AI directly on financial or operational data is

that enterprises quickly run into problems around semantics, governance, scale,

and cost. For example, finance teams rely on very specific

business logic. Which version of the plan? Which hierarchy?

Which allocation rule? Which scenario? Which assumptions?

Without that context, AI can generate inconsistent or misleading outputs.

And then there's scale. Enterprise planning involves massive data sets,

complex calculations, write-back, approvals, workflows, and

auditability. That's not what general-purpose LLMs were designed to manage.

At Board, we believe AI becomes enterprise-ready only when it's grounded in

governed planning semantics and deterministic business logic.

That's why Board is the trusted planning foundation for AI.

Your AI investments become dramatically more valuable when they understand the

business context behind the numbers.