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Getting AI ready in 2024

Getting AI ready in 2024

AI hit the mainstream in a big way in 2023, however for most businesses little or even no real impact has materialised. That's neither a failure of AI itself or business operations - new technology naturally needs time to mature before it is widely adopted. Sensible businesses will identify problems and carefully seek out the right solution, rather than taking an "exciting, new solution" and looking for a problem to solve with it.

What is clear however is that this new technology is maturing fast and will make a huge impact over the next few years. Some businesses will capitalise and cement their growth in the market for years to come, and inevitably some will fall behind and be outmanoeuvred by more efficient competitors. Our strategy for 2024 is focused on ensuring that both our customers and Ferrio land in the former category.

We'll use the term "data" a lot in this article. By data we don't mean 1s and 0s or bits and bytes or "big data". Data means simple business facts that are stored in a system, like "Bill is visiting Acme Corp to repair an A/C unit at 9am tomorrow", or "we have 29x ABB fuses in stock". We're trying our best to demystify tech, but it's not always easy!

What impact will AI really have?

For the vast majority of businesses, AI is not going to change the world. It will be another powerful tool in the forward thinking business' arsenal and will be one important new piece in the fundamental puzzle: selling, then delivering products and services.

Our use cases for AI should be solving problems that software is not already good at solving. Automatically calculating an invoice based on contracted rates? Good software will already do this accurately and reliably. Deciphering and categorising a poorly worded email from a client into an actionable job or task? This is the kind of problem where software will fall short and AI will come into its own.

AI is ultimately the next step on the automation journey, and will compound on the impact software has already had on businesses:

  1. Greater efficiency, particularly in back office processes.
  2. Faster insights and analysis of performance.
  3. Fewer staff needed for better results.

What AI will not necessarily deliver is higher quality data, and that's why AI readiness is so important. 

Why invest in AI readiness?

It's still pretty common for businesses to find that their processes are built on a collection of semi-related spreadsheets in Sharepoint or Google Drive, even when leadership thinks they aren't. AI works best when working in a controlled environment with clear rules, just like any other software. AI can't read minds and will have as much luck figuring out a data minefield like this as a human going into the task blind, but where the human would say "this is a mess, I can't do this!", an AI might just give you the wrong answer to a critical question.

AI is not going to take messy or inaccurate data and make it clean, and AI is not going to deliver return on investment if it does not have access to clean data.

We'll use an example from our own strategy to explain this better. We believe that in the next few years it will be possible for AI to provide custom software development services. The technology is not there yet, but having assessed the current rate of progress and the advantages that no-code development offers, we think it's pretty close ("no-code development" means software that is built without writing code, i.e. using drag and drop interfaces). In preparation for this we're building a dataset using our own projects:

  1. An AI transcribing tool (currently Fireflies) summarises discovery calls with clients.
  2. Once we have enough information we produce a requirements scope, which is linked to the discovery summaries.
  3. On completion of the project, the configuration of the no-code app is snapshotted and linked to the scope and discovery summaries.
  4. Over time, we train an AI model (likely GPT) on this data to produce a scope (for human verification) then an app from the initial discovery call, allowing us to deliver even faster, more cost effective solutions to our clients.

Even though the technology for step 4 still needs more work, as soon as it is ready we will have all the training data required to hit the ground running.

How can we get AI ready?

From the article so far you can probably guess what we're going to say here: get your data in order. This is something most businesses should have been doing for a long time but the benefits have been less clear, particularly for those with less than 100 employees. So what does "get your data in order" mean?

  1. Create a Single Source of Truth: For the data you have in off the shelf software i.e. Hubspot and Xero, create a single database to put all this data in one place. If the software you are using does not make your data available to you automatically i.e. through an API, look to replace it ASAP (An API is the most common method by which data in a software application can be accessed automatically).
  2. Move away from spreadsheets: The reason businesses use spreadsheets is their flexibility. The reason businesses need that flexibility is because the software they have doesn't do what they need it to do. With no code platforms like Airtable and Noloco, custom software is more cost effective than ever. We have customers with less than 5 employees who have entirely custom software suites. Replace your spreadsheets with custom software, which connects to your Single Source of Truth.
  3. Digitise every process: This is one step of AI readiness that AI itself can actually help with! Think about our internal AI development example - we are using AI to turn our conversations with customers into data, which AI can then use to deliver results. Any process you have that is not digitised will not benefit from AI adoption.

Once your data is in order, it is also essential to understand what is possible. Will AI increase the output of your sales team? Absolutely. Will AI let you fire your sales team and still triple sales? Absolutely not (or at least almost certainly not, never say never). Again, thinking of the classic "when you have a hammer, every problem looks like a nail" analogy. Make sure to understand AI's capabilities well enough to identify when AI is the best solution to a problem your business has.

How can Ferrio help?

Naturally, this is how the question is framed in your head by now.

We're on an AI journey ourselves, and everything we learn on this journey directly benefits our customers. Over the course of 2023 we have thoroughly investigated what AI means for us - how it changes our market and how it changes our processes. Fundamental to that is how AI impacts our customers.

The great thing about pursuing AI readiness is that the benefits are far from limited to what AI can deliver. Once your business data is "in order", you won't just be AI ready but automation ready. With or without AI you can automate even complex tasks, removing barriers to growth. Data analytics tools have been accessible to even the smallest of SMEs for years before the arrival of AI and have transformed strategy and delivery.

If you want to discuss AI readiness with us, no strings attached, just contact us via the form at https://ferrio.com/#cta. Our team are always available to chat and offer free advice. We just love solving problems with simple tech