The role of technology and innovation in the business world is becoming exponentially important. Companies are overwhelmed with technological advances and have a hard time keeping up with all innovations in the tech world.
To adopt and deploy new technology in business operations, organizations have to invest their resources in research, training, and integration. That’s the reason why a lot of enterprises are reluctant to adopt novel technologies like AI and machine learning.
However, is this still the company’s decision to adopt AI?
AI and its surrounding technologies hold the power of transforming businesses and industries. The impact AI can create is so immense that organizations can’t say no. Over the last few years, we have witnessed the fast growth of AI and machine learning. The technology will continue this momentum in at least a few more years until it finally becomes standard in the business world.
At the current stage, companies are taking in AI and machine learning with the hope to create direct revenue. Later on, however, enterprises will have to go beyond that. As the computing power and AI/machine learning advance, businesses will find themselves trapped in a never-ending cycle that forces them to continuously invest more in R&D and deployment of AI to stay on par with other competitors. If they fail to keep up with their peers, the price may be their market share and customers.
Big data is also growing fast and empowering AI and machine learning more than ever. AI is developing its ability to give more accurate data-driven decisions. When the technology gets mature, businesses will be more dependent on AI-enabled tools. At that point, sitting on the fence is no longer an option.
For the time being, the skills gap and compute power are some of the most critical problems in AI adoption. Besides, many enterprises are still skeptical about machine intelligence, data-based decision-making; they still rely on the more traditional approach of experiences and intuitions. However, the reality is proving that it is no longer an appropriate way to read the market. AI and machine learning tools are doing a better job at understanding the statistics.
In short, businesses need to adopt new technology like AI, big data, machine learning, etc. Not all companies have to invest a pile of money into their AI initiatives. The most cost-effective adoption strategy is to get what is right for your organization, in terms of size, needs, budget, and industry. If a company constantly tries to reach way far beyond its needs and abilities in the game of AI, it may actually be falling out of the race instead of winning it.
Nonetheless, no matter how far AI gets, businesses can’t be totally dependent on the technology. The world is not all about numbers; therefore, enterprises will need to maintain and improve their experiences and intuitions while exploiting technological advances. AI is powerful, but eventually, it is humans who create it so AI is not perfect. There will be a situation that needs the experience—based and intuitional decision from a human. After all, the balance between human and machine is what businesses should aim for.