How can startups get to grips with AI for the first time?

In the post-COVID corporate space, investment in new technologies has shifted up a gear. To meet a whole host of new needs, organizations have been looking to platforms at the cutting-edge of innovation to support their business requirements – and at the top of this list is artificial intelligence (AI).

The scope for investment in AI-driven technologies is huge: in just four years, between 2015 and 2019, the number of organizations investing in AI grew by a staggering 270%. This should be proof enough that in the months and years to come, automation will be key to sustainable digital transformation strategies, enabling organizations to stay ahead.

However, as much as vendors like to sell their products with plug-and-play simplicity, the truth is that these technologies can be incredibly complex. In a sector brimming with new solutions, it can therefore be difficult for young businesses to make genuinely objective decisions about how best to automate their operations. So, what should organizations consider before taking the leap?

Is AI right for your business?

Although the opportunities are endless for AI when it is implemented effectively, particularly for early-stage organizations, it will not be right for every business. Sometimes, the timing just won't be right, and businesses will not have a pressing need for automation. However, it can still be easy for firms to be taken in by market hype.

Undoubtedly, when leveraged effectively, AI can be a game-changer – offering the potential for new leads and greater revenue, among other advantages. However, business leaders should ask themselves what exactly they are expecting a new AI solution to deliver, rather than investing in AI for AI's sake.

For example, if an organization is looking for enhanced data analytics to drive their operations and offer a competitive advantage, then AI could be the perfect solution. Likewise, if AI has already been proven to deliver value in another area of your organization, such as automating customer communications through sophisticated chatbots, then now might be the time to broaden AI's reach. However, if there is no clear answer to this question, then it might be a better idea to look for alternative means to bolster your operations.

Business leaders should also watch out for technologies that buy into their own hype; indeed, solutions that label themselves as 'AI-driven' aren't always more effective or sophisticated than traditional pieces of software. With such an oversaturated market, it can be difficult for firms to cut through the noise and discern which products will deliver tangible benefits for their organization. As such, it would be wise to ensure that vendors can demonstrate sufficient proof of value (POV) before racing ahead with new investments, to determine the expected outcome for introducing new AI solutions.

Particularly if startups are looking to purchase custom-built products, I would advise allotting some extra careful consideration into investment procedures. Throughout the process, vendors should be able to present an in-depth strategy, outlining how AI will deliver solutions to specific business needs. This should take all aspects of your organization into account, including your company's data and long-term goals, to ensure that you receive a good return on your investment – after all, startups will likely have less in the way of budgets compared to their larger counterparts.

More haste, less speed

Even if the time and price is right to go ahead with AI investment, startup founders should resist the temptation to move too quickly. Indeed, the best implementation strategies recognize the fact that it is often best to take on new tech slowly, but surely.

To begin, it can be a good idea to set out a timescale, alongside specific milestones your organization hopes to achieve in a series of measured stages. In this way, startups will be able to iron out any niggling issues, as well as enabling staff to get to grips with new tech. For example, if a particular aspect of a custom AI solution isn't functioning exactly as intended, ample time can be taken to communicate this to the vendor, who can then make the necessary adjustments before ploughing ahead with the next stage of the deployment journey.

Implementing AI incrementally will also allow founders to invest in equipping their organization with the right skills and talent to manage new tools. This should entail conducting a skills assessment throughout your organization to determine where knowledge can be improved in-house, and where gaps can be filled with new talent. Thankfully, it seems like organizations are already catching wind of this, with almost half (48%) stating that they would be sending employees for AI-related training in 2021.

No good AI without good data

Finally, startups should get their data in order before investing in AI – doing so will ensure that they are able to fully realize the benefits of new tech when it arrives.

As products with AI and machine learning (ML) at their core learn from the information they are provided with, it is vital these technologies are equipped with a litany of data so that they can provide fully informed insights and accurate modelling.

And it isn't just quality that is important. It is equally important that data – whether this is collected to learn more about your customers, or your internal affairs – is appropriately collected. Not only should the data be relevant, but it should also be captured and administered correctly – this will make for well-trained AI, and make sure that startups get the most out of new tech.

Ultimately, AI looks poised to deliver meaningful change and improvements to organizations of all sizes, and small businesses are no exception. Offering the potential to drive resilience and improve productivity, amongst a spate of other benefits, I have no doubt that many young organizations will opt to invest in these technologies in the months and years to come. And as they do, founders would do well to remember one simple thing: it's not just what you adopt, it's how you adopt it that matters.

Author: Ero Georgiades, Chief Operating Officer of Fountech Solutions

Ero Georgiades is the Chief Operating Officer of Fountech Solutions, an AI consultancy and development company which helps businesses of all sizes, and across all sectors, to integrate AI solutions. It designs and develops novel AI solutions, before offering extensive support throughout the implementation stages.