4 AI mistakes your business makes

Many companies that implement AI solutions make the same mistakes as each other and I see it time and time again.

Here at the top mistakes that companies make when implementing AI and how you can avoid them.

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Presented by Symbl.ai and Deepgram

Learn more about Symbl.ai here.

Learn more about Deepgram here.

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1. No pre-work or discovery

The biggest mistake is that they don't do any (or hardly any pre-work). They don't do any of their own discovery. And that can mean that you get caught up in all kinds of knots.

Without figuring out for yourself what business problems need to be solved, in what order, what the impact of solving them will be, who you need to solve them with and how technology is intended to enable that mission, then you're just dwindling around the ether hoping for something good to come about by chance.

Without this, you're not in control of your own destiny. You have no choice but to outsource this part to another company. A company who's motivation and incentives may not be aligned to yours.

2. Not aligning business stakeholders and influencers

A knock-on effect of no. 1 is that you then fail to align the parts of the business that need to be aligned on a strategy like this.

AI is not a quick fix, point solution. It is a long-term strategy. You need to have all different parts of the business aligned on what you're trying to achieve and how you're going to achieve it. You'll need support from IT, marketing, finance, sales, business units; the whole business. They all have a role to play, and increasingly as your strategy unfolds.

3. Not prioritising use cases and channels

The third thing is that you don't do any pre-work on your use cases and channel priorities.

Where does it make sense to start? What are your short-term priorities? And what use cases are going to enable you to prove the value of this kind of technology? What will solve your business or customer problem best?

What's your current level of AI maturity and what kind of projects will enable you to build your knowledge and skills?

Which projects and use cases align best with a business problem that's most acute? Which align with your wider business strategy?

All of these are considerations that some companies completely overlook and thus choose the wrong place to start.

Choosing the wrong place to start your journey can lead to backtracking, time-wasting and further costs later. Imagine climbing the wrong mountain.

4. Not gathering requirements

The third thing that's skipped is requirements gathering. Basically, making sure that you know what you need to begin and to achieve success.

Without knowing what you're looking for or what you need, how can you hope to find success? A hiker has requirements before they take one foot on a track. A map, a compass, some suitable footwear and clothes, some rain gear, some food, GPS, a planned route. You can't hope to proceed without requirements.

You don't need to have them completely nailed absolutely, and working in an agile methodology is beneficial, but you need to at least have some detail on the two types of requirements you're going to need:

External capabilities

These are capabilities that you don't have at your disposal right now. It could be technology requirements i.e. technology that you know you'll need, but don't have.

Most companies don't think about those capabilities in enough detail to be able to adequately select a technology partner, capability or bridge their skills gap.

Many companies actually go out to tender to speak to vendors in order to gather requirements, which is ass about face because you end up with requirements that align perfectly to those vendors. Vendors that may have interests that aren't aligned to yours.

Internal capabilities

Then there's business requirements. Internal capabilities.

There's going to be requirements internally within your organisation that you're going to need in place to implement a successful solution.

That could be resource requirements. It could be skill sets. It could be line of business technology requirements. It could be data access requirements, data creation requirements, governance requirements, and a whole bunch of other things that many people overlook.

They think that AI is an out-of-the-box solution that doesn't require any organisational support, buy-in, governance, strategy or structure, which couldn't be further from the truth.

Pause first

So, without doing some due dilligence, and some good discovery work before you look to implement a solution, you will go to market too early. You will likely find the wrong solution. You will be influenced and swayed by vendor interests instead of being influenced and persuaded by business interests. And ultimately, the chances of failure are greatly increased.

So before you implement an AI solution in any part of your business, just pause for a second and make sure that you've done the right kind of discovery, the right kind of pre-work and make sure that you're ready to take the journey.

And if you're struggling and need some assistance or guidance, please do reach out here or on LinkedIn. It's what we do.

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