How can a business get prepared to use AI optimally?

How can a business get prepared to use AI optimally?

There are companies out there doing a great job with utilizing AI and other innovative technologies. Some others, well, not that great. What’s the difference between them? What is the winning strategy? There is no clear recipe for success but in this article we share everything we can suggest to a business leader who is dedicated to innovation but would also like to avoid the pitfalls.

These days, every single business is, in a way, a tech business. All business leaders experience the pressure and fear of missing out on using current technologies in the best way possible. If you want to explore further how to incorporate AI into your business, check here. But for now, take a look at these speeding freight trains of trends that have blazed past through the last few years:

  • Inbound marketing
  • SEO
  • Big Data
  • Cloud
  • IoT
  • Blockchain
  • Drones and Robotics

and the many different uses for AI, like NLP, RPA or Machine Learning.

The key matter is that these are not only possibilities that will be handled by ‘the IT department’.

It’s more and more about the core business itself. That’s why they require leadership capacity in the decisionmaking, and the full cooperation of the whole organization to achieve successful implementations.

This requires a holistic approach, which in itself is a great challenge as business leaders need to balance it with managing the day-to-day activities.

Beyond all that, if it’s all connected, how can you measure ROI?

Deploying AI is very much unlike installing a new, more powerful engine or more reliable bearing. It’s a complete technology switch, like going from diesel to electric, but even this analogy feels somewhat off.

Some business leaders, who are not living and breathing the most up-to-date tech solutions often stil think that AI is something ‘IT’ should be able to handle. However, because digitalization is all but complete, it means that every aspect of the operation generates at least some data. This data can be used as fuel for ‘machine spirit’, which can then elevate the business to a new level as a whole. Sounds like a fairytale, but in its simplicity, it describes the situation well.

AI is not a mean for an end - it affects the core operation of every business

So what can a responsible business leader do to build the optimal process leading to his organization becoming an ‘AI company’? How can you utilize these emergent, disruptive opportunities optimally?

We are always trying to stay in the loop with following AI experts globally, and we add our own assumptions coming from the experience of all the AI projects we already closed successfully. Currently, we can answer those questions above in the following four points:

1. Dedicated resource

There needs be someone in your organization who can identify with this mission passionately, and they should be officially assigned to the task. They will be the contact point for the AI consultancy and development partner team. This colleague should know the inner processes well and use this knowledge to uncover the wealth of opportunities. They don’t need to be autonomous decisionmakers, or to have software development skills. All they should have is dedication and commitment to transparency.

This character is often called the ‘champion of the cause’. AI projects are holistic, which carries a lot of risk. The projects can get derailed, boggled down in details of certain aspects and lose focus if it’s just another box to tick on the checklist of the C-tier, who have obviously been busy enough already. This is why you need a real assignee with a critical eye on things who turns every stone and removes all obstacles to achieve the optimum.

This is somewhat similar to what a Product Owner does in the IT world. So think of this role as an ‘AI owner’. AI is not about designing software tools, it’s more like a process, an approach and a philosophy. It needs its own ambassador within the halls.

2. Go from the simple towards the complex

Now we take what maybe feels like a U-turn: no matter how all-encompassing AI adoption is, you need to strive for some early results. Something that can be measured and where the advantage is clear as day. This boosts confidence, morale and trust within the organization towards AI, which will be required for everyone to feel it’s not just a ‘hassle’, that there are tangible benefits. These early results can be very small, quality-of-life changes and functions, because the big projects possibly take long time anyway.

3. Innovation partnership will likely be the way to go

In Hungary, we know very few companies that possibly have the capability to do AI development in-house. Globally, the situation is not so different in the sense that ERP cloud projects are usually also done via consultancy and outside support, just think along the lines of AWS or Microsoft Azure.

A consultant developer team can be your innovation partner indefinitely with gradually building trust backed up by NDA-s. Whereas an employee can just get signed by your competition at any moment. It’s probably better to work with the experts and specialists in the case of new technologies.

4. AI identity

In the end, the whole organization will become an AI company. New technologies will become their DNA. Again, this goes against the assumption that AI is an ‘IT project’, something that has a start and an endpoint, like, moving systems into the cloud or designing and implementing new security protocols.

Successful business leaders get rid of ‘transactional’ thinking - AI is more like an organization restructuring process, and it’s unlike something you can just manufacture and present in a box.

The AI expert team and the company should work together in planning the product, starting with the simple and progressing towards the complicated. This is not something you want to outsource completely - the business itself should change with it, thus becoming an ‘AI company’.

There are three key thoughts the business leaders need to internalize to do this successfully:

1. ‘We understand that we need to change.’

2. ‘We are ready to learn new things.’

3. ‘We will do it our own way, and our expert partners will help us with it.’

The best way to have someone in the senior management with the clear aim: ‘we want to create AI products and we want the best help we can get’. This is the polar opposite of the ‘we want you to build this tool for us’, which artificially limits the value that could be gained.

Through the consultancy process, the products are ‘invented’ together, completely organically. The solutions open up and show themselves to the leadership as possible directions of taking the business to a higher level.

As a business leader, sooner or later, you will need to meditate on these two basic questions:

‘What happens, if we ignore AI?’

‘What are our needs and challenges?’

In the end, always the organization will be the one to realize what it needs. And the experts are there to empower this exploration process with good questions.

There are a miriad of decision points the company will progress through, like: who leads the team responsible for the developing solutions for the innermost needs of the company? Do you need new competencies? What will be the key metrics? This is one more reason why you need a ‘champion’ who oversees the work on the AI projects.

This is how the winning AI strategy will be shaping up - this gives you the key to the future!

If you are interested on how we create tailor-made AI solutions together with our partner companies, let us know! We would be more than happy to know about the particular challenges your company is facing in AI deployment.