Opinions expressed by Entrepreneur the collaborators are his.
Artificial intelligence (AI) makes 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 fast; many humans already have fellow robots.
TippaPact | Shutterstock
This is a trend that affects almost every industry. Last year, McKinsey revealed that the adoption of AI continues to grow globally; in turn, as AI-based businesses have become more commonplace, the tools and strategy for maximizing the benefits of AI have become more sophisticated.
In the healthcare world, for example, AI platforms can be key to collecting and analyzing unmatched levels of data to diagnose disease. Automating this process and working closely with the data helps doctors make better, smarter, and faster decisions. Those who work closely with AI reach a point where their use can be incorporated into training, reducing pressures on a wide range of processes and responsibilities, such as rationalized symptom screening and triage.
But AI is not a silver bullet and should not be treated as a solution to fix everything. It is wrong to rush into introducing AI solutions without properly understanding how technology works and how it will affect its role in processes.
This is one of the main reasons why AI projects can often fail, and Gartner predicts that 85 percent of AI projects fail, and just over half (53 percent) of projects fail. from prototypes to production. With the right approach, however, more companies can successfully integrate AI into their operations.
1. Understand your business requirements.
First of all, it doesn’t make sense to automate something for this. The importance of knowing what not to automate cannot be overstated. To establish the best foundation, entrepreneurs should conduct an MRI-style audit of their business to assess their needs and capabilities. This will reveal what painful points could be alleviated with AI-driven solutions.
The basis for this is to identify which business elements will benefit most from cognitive applications, such as predictive knowledge and automated processes. Small, repetitive, and monotonous tasks, such as frequently asked questions in customer service teams, are where automation can really shine.
2. Prepare your data.
Algorithms are only as good as the data they feed into, so it’s important to have a firm idea of what you want to achieve and solid examples for the algorithm to learn. As such, before attempting to integrate AI information into business decisions, it is critical to ensure that the data is of high quality and clean.
In practice, this means striving to ensure that the data is as accurate as possible and without inconsistent information, providing them with the necessary attributes for an algorithm to do its job well. Also, preparing data is not a unique thing. For continuous best results, data must be routinely organized, updated, and expanded, and strong human review measures are essential.
This means that companies need to ensure that those who oversee AI decision-making are properly trained, equipped with the skills and knowledge to override automated action when needed.
And don’t forget about data protection. AI governance processes should include monitoring the level of human input to meet the requirements of data protection laws.
3. Embrace augmented intelligence.
The key to this is to make sure that any AI is paired with the right people to create a human-centered partnership – the so-called augmented intelligence. In recent years, much work has been done to ensure the sustainable creation of AI, such as the European Commission developing ethical guidelines for reliable artificial intelligence. Microsoft’s six principles for AI include fairness, inclusion, reliability, and security, transparency, privacy, security, and accountability. Other tech giants like Google and IBM have custom codes of conduct.
AI should not be seen as an existential threat to people, but as a companion. The two can work harmoniously with each other, with AI improving knowledge, experience, and time management. As organizations around the world increasingly embrace digital technologies, leveraging AI capabilities has the potential to greatly improve outcomes.
As AI becomes more commonplace, developers and other technology professionals are working more closely with the company’s non-technical managers. Achieving optimal business results requires critical thinking, problem solving, and interpersonal communication skills in all departments.
4. Build confidence in AI.
Of course, having great power carries great responsibility, which is why building trust in AI is critical. One of the biggest challenges in integrating AI is making sure people use technology responsibly. Companies that rely on AI must hire staff trained to use the technology properly.
In healthcare, for example, ethics and building trust are vital to the medical adoption of AI; Maintaining the ethics of AI is based on prioritizing patient privacy, while obtaining useful patient information to progress.
To support this, AI developers need to be transparent about how products are designed and run before they reach the hands of the end user. This should lead to AI developers providing precision testing as well as an insight into their technology development process.
On this basis, it ensures that AI is inspectable, so that relevant stakeholders can see how the digital transformation process is progressing and how it can be changed if something goes wrong.
5. Find the right partner.
When considering how AI can help grow your business, there are several options to consider, but hiring in-house technology talent doesn’t have to be the answer. After all, for companies 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 a specific niche. They provide all the crucial components with cutting edge technology.
In addition, startups can help alleviate some of the key challenges involved in trying 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.
In short, technologies are only as good as the companies that build and implement them. However, with prudence, AI can reveal not only the limitations of a company, but also, critically, its strengths.