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What is generative AI consulting and do I need it?

Short answer

Generative AI consulting is advice and implementation around tools that read, write and summarise language, such as large language models. In practice that means automating work built on documents and messages. Quoting, invoice coding, order entry, customer replies and finding answers in your own records. You need it if a few people in your business spend their week doing that kind of work by hand.

Generative AI is the reason AI consulting became relevant to ordinary businesses. Before it, AI was mostly for companies with a data science team and a lot of structured data. After it, any business with a pile of invoices, quotes, orders or emails has something worth automating.

What it means in plain terms

Generative AI refers to models that work with language. They can read a document and pull out what matters. They can write a draft from a set of facts, summarise a long thread, or find the relevant passage in a pile of records.

That is exactly the shape of most office admin. Read this, type it in there. Look up that, write a reply. Find the document that says what we agreed. Until recently none of it was automatable, because it involved reading and judgement. Now the reading can be automated and the judgement can be left with a person.

What generative AI consulting involves

Finding the document heavy work in your business that consumes the most hours. Working out which of it is consistent enough to automate reliably. Building the automation against your real systems and testing it against your own history. You know the error rate before it goes live. Designing the queue for the things it is not sure about.

Then teaching someone in your business to run it.

Where it works well

Reading inbound documents and putting the data in the right place. Invoices, orders, delivery dockets, claims.

Drafting from your own history. Quotes, proposals, customer replies, reports, in your voice and your template, for a person to approve.

Answering questions from your own records. Procedures, past jobs, pricing precedents, contract terms, with the source cited.

Checking one document against another. A subcontractor claim against the contract. A supplier invoice against the purchase order.

Where it does not

Anything where the inputs are chaotic and the volume is low. The setup cost will not pay back.

Anything where a mistake is catastrophic and cannot be caught by a human review step. Generative AI is probabilistic. It proposes, and a person decides.

Anything a well built product already does for a monthly fee.

Do you need it

Ask who in your business spends most of their week reading things and typing them somewhere else. Or who writes the same kind of document over and over. If you can name them, you probably do. If you cannot, you probably do not yet.

Related questions

Questions

How is generative AI different from other AI?

Older AI mostly predicted numbers or categories from structured data, such as demand forecasts or fraud scores. Generative AI works on language and documents. It can read an invoice, draft a quote, summarise a contract or answer a question from your own records. That makes it useful for admin work that was previously impossible to automate.

What can generative AI do for a small business?

Read inbound documents and put the data where it belongs. Draft quotes, emails and reports in your voice from your own history. Answer staff questions from your own procedures and records. Check documents against each other, such as claims against contracts. All with a person approving the result.

Is generative AI safe to use with our business data?

It can be, with the right setup. Data must stay in systems you control. The model must not train on your data. A person must approve anything customer facing. A consultant must be able to explain exactly where your data goes and why.

Do I need a generative AI strategy?

You need a short list of the two or three pieces of document heavy work that cost you the most hours. Then a plan to automate the first one. Call that a strategy if it helps get it funded.

Next step

We map where your hours go and price the work that is worth automating.