92% of large companies achieve notable returns on their investment in artificial intelligence. Businesses often adopt AI for simple reasons: it reduces human error, automates repetitive tasks, and improves the customer experience with deep personalized insights. The effort pays off—more than 80% of IT professionals worldwide in marketing and sales believe that AI leads to cost reductions for their organizations. To reap these benefits, a strategic, holistic approach is key.
However, in the wake of fierce competition, new regulations, and rapid-fire developments like ChatGPT, organizations are scrambling to figure out AI. Understanding the top five barriers to AI adoption will help your organization prepare to deploy AI successfully.
When you type a sentence in an email, sometimes your email composer will suggest the end of a word or a sentence. Based on context clues, natural rhythms, and the language used, there are only so many words that could logically follow the last one you typed. By typing an ordinary email, you just interacted with AI.
Whether you’re composing an email, generating keywords for an SEO article, or creating an automated email workflow, AI has likely touched some part of your work life. However, when it comes to organization-wide implementation, it’s easy to feel lost and overwhelmed.
Artificial intelligence provides an endless sandbox for experimentation—which is paralyzing enough to stop many organizations before they begin. AI technology is complex, expensive, and incredibly powerful—which means that organizations must understand what’s right for them before making an investment.
The barrier of not knowing enough about AI or its deployment is only overcome through knowledge and experience. Many experts recommend conferences where you can network with other companies that use AI, learn from subject matter experts, and connect with AI specialistsor vendors.
According to Harvard, change management strategies often fail because leaders focus on technology instead of people. In fact, behavior at the top is a primary indicator of whether organization-wide change will be successful. Employees need hands-on guidance through big changes, with a focus on anticipating consequences and minimal disruption.
The mantra for most technological advancement is simple: machines do it better. Whatever ‘it’ may be, technology does it in less time, for less money, with higher accuracy. When implementing artificial intelligence, workers are rightfully worried that their jobs are disappearing.
The ramifications of new technology are real. After all, repairing fax machines or making cassette tapes aren’t popular careers anymore. New technology has replaced those jobs—but it’s also created even more new jobs in their wake.
Implementing AI is equivalent to implementing a change management strategy. It requires education, support, consistency, and a thoroughly considered transition plan that prioritizes people first.
The cost of deploying AI is prohibitive for many organizations. After all, it requires a significant investment in new hardware and software, education for existing employees, new hires, and more. To counteract this huge expense, many experts recommend that companies start small and scale gradually.
Start by selecting a single department or business as your test subject. Deploying a pilot AI program can ease corporate anxieties about budget, uncover opportunities to correct course, and provide small wins that justify investment on a larger scale.
However, big results often require an equal investment. In a recent McKinsey survey, 63% of respondents reported a 5% annual revenue increase thanks to AI adoption. As organizations evolve, new capabilities that save money and boost productivity are increasing revenue. However, an article by Kiplinger suggests that limited AI adoption doesn’t translate to significant measurable growth in the real world. Instead, companies must make a real commitment to see a return by using at least 25% of the AI tools available to them.
While the scale necessary for this approach can be intimidating, remember that small investments can pave the way for a larger one. But if your results aren’t as impressive as previously hoped, remember that holistic AI adoption is the key to seeing more impressive results. Partnering with a reputable AI vendor is another way to cut costs, too.
Artificial intelligence exists because of data. Most of it revolves around consumer data which means that AI is a high-stakes game. If your systems are hacked, or customer information is exposed, your organization’s image will suffer. Depending on federal or state regulations, you may also face legal or criminal penalties. When dealing with massive amounts of data, theft, illegal access, and cybercrime are big risks.
Consumers—in fact, 62% of them—want to give you their data if it means they’ll get an improved digital experience. Of course, transparency with consumers is the first step. How are you using, processing, and storing consumer data?
To protect the data necessary for successful AI adoption, ensure compliance with relevant data protection rules and regulations. Data encryption, access limits, and recurring security audits are a great place to start. Implementing an audit, risk, and compliance process is also critical to make sure your bases are covered–and may even be necessary to comply with regulations and industry standards.
It can be tempting to trust artificial intelligence over human intellect. After all, ‘human error’ is responsible for more mistakes than an automated algorithm. But it’s crucial to remember that artificial intelligence is only as good as the people creating, feeding, and using it. When using AI, the accuracy of the original information, context clues, and implicit bias must be accounted for. Nothing should be implicitly trusted. In fact, only half of employees fully trust AI in their professional lives.
Successfully implementing AI can take many forms, especially when tackling big problems on a limited budget. Some vital solutions include:
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