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5 Tips for Integrating AI Into Your Business Rushing to introduce AI solutions without properly understanding how the technology works and how its role will impact processes is misguided. Here's how to take the right approach.

By Piotr Orzechowski

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Artificial Intelligence (AI) is making the workplace more efficient. By automating time-consuming processes, teams have more time to focus on more meaningful and strategic work. And the pace of change is swift; many humans already have robot colleagues.

This is a trend that is impacting almost every industry. Last year, McKinsey revealed that AI adoption continues to grow globally; in turn, as AI-powered businesses have become more common, the tools and strategy to maximise the benefits of AI have become more sophisticated.

In the world of healthcare, for example, AI platforms can prove instrumental in gathering and analysing unparalleled levels of data to diagnose diseases. Automating this process and working closely with data helps doctors make decisions better, smarter, and faster. Those working closely with AI get to a point where its use can be incorporated into training, easing pressures across a wide range of processes and responsibilities, such as streamlined symptom checking and triage.

But AI isn't a silver bullet, and it shouldn't be treated as a fix-all solution. Rushing to introduce AI solutions without properly understanding how the technology works and how its role will impact processes is misguided.

It's a leading reason why AI projects can often fail, with Gartner predicting that 85 percent of AI projects fail to deliver, and little more than half (53 percent) of projects make it from prototypes to production. With the right approach, however, more businesses can integrate AI successfully into their operations.

1. Understand your business requirements.

First things first: there's no point automating something for the sake of it. The importance of knowing what not to automate cannot be overstated. To lay the best foundations, entrepreneurs should carry out an MRI-style audit of their business to assess its needs and capabilities. This will reveal which pain points could be relieved by AI-powered solutions.

Core to this is identifying which business elements would benefit the most from cognitive applications, such as predictive insights and automated processes. Small, repetitive, and monotonous tasks – such as frequently asked questions in customer support teams – are where automation can really shine.

2. Prepare your data.

Algorithms are only as good as the data they're fed, which is why it's important to have a firm idea what you're aiming to achieve and strong examples for the algorithm to learn from. As such, before attempting to integrate information from AI into business decisions, it's paramount to ensure that data is high-quality and clean.

In practice, this means striving to make sure the data is as accurate as possible and devoid of any incoherent information, equipping it with attributes necessary for an algorithm to perform its task well. What's more, preparing data isn't a one-time thing. To continually achieve the best outcomes, data should routinely be organised, updated, and expanded, for which robust human review measures are essential.

This means that businesses must ensure that those monitoring AI decision-making are appropriately trained, equipped with the skills and knowledge to override an automated action where necessary.

And don't forget about data protection. Governance processes for AI should include controlling the level of human input to meet requirements dictated by data protection laws.

3. Embrace augmented intelligence.

Key to this is making sure that any AI is paired with the right people to create a human-centred partnership – so-called augmented intelligence. In recent years, lots of work has been done to ensure the sustainable creation of AI, such as the European Commission developing the Ethics Guidelines for Trustworthy Artificial Intelligence. Microsoft's six principles for AI include fairness, inclusiveness, reliability and safety, transparency, privacy, security, and accountability. Other tech giants like Google and IBM have bespoke codes of conduct.

AI shouldn't be viewed as an existential threat to people but instead as a companion. The two can work harmoniously alongside one another, with AI enhancing knowledge, expertise, and time management. As organisations across the world increasingly embrace digital technologies, harnessing AI capabilities has the potential to greatly improve outcomes.

As AI becomes more mainstream, developers and other technology professionals are working more closely with non-technical managers across the company. To achieve optimal business results, critical thinking, problem-solving, and interpersonal communication skills are needed across all departments.

4. Foster trust in AI.

Of course, with great power comes great responsibility, which is why it's critical to create trust in an AI. One of the biggest challenges when integrating AI is ensuring that people are using the technology responsibly. Companies that rely on AI must employ trained personnel to use the technology appropriately.

In healthcare, for example, ethics and trust-building are vital for the medical adoption of AI; keeping AI ethical rests on prioritising patient privacy, whilst still getting useful patient information to progress.

To support this, AI developers need to be transparent about how products are designed and function before they reach an end-user's hands. This should entail AI developers providing evidence of accuracy as well as insight into their technology development process.

Underlying this is making sure that AI is inspectable, so that relevant stakeholders can see how the process of digital transformation is proceeding, and how it can be changed if something is not right.

5. Find the right partner.

When considering how AI can help grow your business, there are several options to consider – but hiring in-house tech talent doesn't have to be the answer. After all, for businesses looking to integrate AI into their operations, it's no secret that startups and corporations often go together.

This is because, while most companies could benefit from a wide range of AI technologies, startups tend to focus on one specific niche. They provide all the crucial components with cutting-edge technology.

Moreover, startups can help ease some of the major challenges that come with attempting to implement AI successfully, such as the pressure to create new roles, hire new skills, collect data, adapt processes, or work in a fast-paced environment. The right strategic partnership can help companies overcome these challenges, allowing them to focus on growing their business and creating value.

Ultimately, technologies are only as good as the companies that build and implement them. Harnessed wisely, however, AI can reveal not just a company's limits but also – critically – its strengths.

Piotr Orzechowski

CEO and founder of Infermedica

Founded in 2012 in Wrocław, Poland, by Piotr Orzechowski (CEO), Infermedica’s AI-driven platform -- which has conducted more than 10 million health check-ups globally -- provides preliminary guidance of medical conditions based on symptoms.

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