Source: Mental Daily

Artificial Intelligence (AI) is the word crowning every conversation and technology necessitating most business expansions. From customer relationship management and forecasting to quality assurance in manufacturing and producing software code, AI has proven useful in enhancing business operations.

According to ABI Research, a global technology intelligence company, there will be over 900,000 businesses that will have integrated AI into their systems before the end of the year.

Despite the massive adoption, not every company is having an easy time factoring the technology into its business.

Challenges of Adopting AI in Businesses

It goes without saying that AI is a complex technology whose adoption is disruptive. First, AI is a customized technology that is made personal to a business using the company’s data. However, to be able to train and build quality AI systems requires large datasets which some companies do not have. This makes it difficult to create AI solutions, let alone make them high-quality.

Secondly, the implementation of AI solutions requires an understanding of the inner workings of the models and algorithms used. This is necessary for both the developers and the organization to better understand the results of the solution.

This can prove difficult, especially for employees working in non-technical departments who will be required to use the solutions in their day-to-day operations.

Additionally, the implementation of AI is certainly a major organizational change that stakeholders in the company may not be willing to adapt to. Executives see the technology as hype whereas employees fear the technology may render them redundant causing them to lose their jobs.

Another major concern is the cost of implementation since AI requires an investment in high-performance technology and software. This has posed a massive challenge to companies especially small ones which have to consider the constraints of the available funding.

Simplifying the Adoption of AI

Source: Bernard Marr

Despite these challenges, AI has proven to be effective in areas where it is employed by saving both time and money. According to a recent report by IBM, the company’s human resource division was able to save 12000 hours over an 18-month period of employing AI for 280 tasks.

Nickle LaMoreaux, the firm’s chief human resources officer said:

“We’ve got over 280 different A.I. automations running inside HR right now. That’s what is different here. It’s making HR more human because we’re spending time on things that matter.”

Therefore, to make the process of AI adoption more streamlined, here are some steps to follow.

1. Understand AI

Even before a company starts overhauling its systems with AI, it is paramount that it understands the technology and its capabilities in the context of the said company. This, therefore, requires that the company familiarizes itself with the technology along with its fundamentals and applications.

This will not only help the company have an idea of where best to employ the technology but will also help in showing employees that AI is meant to help them work better, not to replace them.

2. Define the Company’s Goals

AI is a technology that fits every industry and has a place in almost every company. As such, it is necessary for the company to define the areas it wants to enhance with AI. The company should also be clear on what it aims to achieve by integrating AI into the area.

By so doing, the organization will have a guideline and metric by which to evaluate the success of the solution once implemented.

3. Evaluate the Company’s Capabilities in Implementing AI

Once the goals are in place, an organization should then analyze its ability to implement the solution with regard to manpower, infrastructure, data, and finances. At this stage, the company looks at whether or not it has the expertise to implement the solution in-house or whether it will have to outsource the work.

It also looks at whether it has enough high-quality data that will be used in the development of solutions as well as the hardware and software required for the development of AI models. Based on the outcome of this evaluation, the company can decide to seek a partnership with an AI development company.

4. Develop the Solution

Source: GMS

With all requirements in place, a business can now develop AI models suitable for its business use case. Important to note is that training and testing AI solutions is an iterative process. It will therefore require the evaluation based on the company’s goals and metrics to determine whether it is fit and of benefit to the business.

5. Pilot the Solution

Once the solution and the results of the metric evaluation are acceptable according to the company’s expectations, the solution can then be deployed to a controlled group. This will enable the company to collect feedback from its customers about the service post-AI implementation.

Employees can also assess how the solution is affecting their performance as well as productivity. At this point, the solution can still be tweaked and retrained to better fit the company’s use case.

6. Deploy the Solution

The solution is ready to be fully integrated into the system when the pilot phase is complete and AI has shown its ability to improve the business and its service to its clients.

It is important for a company to strike a balance in the adoption of AI. Doing a complete overhaul of every area could harm the business more than benefit it. The technology should be used to grow the business and expand its operations to reach new markets.

What's the Best Crypto to Buy Now?

  • B2C Listed the Top Rated Cryptocurrencies for 2023
  • Get Early Access to Presales & Private Sales
  • KYC Verified & Audited, Public Teams
  • Most Voted for Tokens on CoinSniper
  • Upcoming Listings on Exchanges, NFT Drops