Interest in artificial intelligence (AI) continues to steadily grow each year. While only 14% of businesses used AI technology in 2019, this number increased to 19% in 2020, and it’s only expected to become more prevalent in 2021, according to research from Gartner.
The ever-increasing interest in AI technology will play a key influence on technology investments for businesses in the near future. However, AI growth requires more than just adopting the latest tech or modeling techniques in the industry. A chief information officer (CIO) will need to create a clear business purpose to invest in this innovative technology, whether it’s scaling AI across the company or transitioning an initial AI solution to production.
AI doesn’t offer a one-size-fits-all solution for businesses, but it can provide answers for particular scenarios or problems in the workplace.
Here are a few key factors that CIOs need to consider in creating a convincing case for using AI technology, while also considering the various obstacles businesses will face while adopting AI technology.
Digital Adoption and Artificial Intelligence Growth
A critical component of any business decision is analyzing the costs and benefits of digital adoption solutions. However, doing this for an AI project isn’t always an easy task. Many AI projects will appear costly without any immediate gains, especially for companies not used to creating a budget for digital adoption solutions.
The ROI for AI projects is influenced by three factors in the workplace.
DIGITAL ADOPTION – Businesses already focused on digital adoption can benefit most from using artificial intelligence, as they already have an advantage by focusing on digital transformation.
INVESTMENT IN AI – An investment in AI can’t be carried with minimum effort, as businesses benefiting from AI are investing much earlier in this technology compared to competitors.
STRONG MANAGERIAL SUPPORT – The vast majority of successful AI projects have support from upper management, as this is closely related to an organization’s culture.
A chief information officer needs to consider all of these factors while calculating the potential costs and benefits of an AI project. Always being upfront with stakeholders is important, as these costs can significantly change over time as the process is explored and refined. It’s also important to discuss a willingness to shut down an AI project if there isn’t a clear benefit to the company.
Artificial Intelligence Requires a Unique Skillset
Talent acquisition is one of the most difficult challenges for businesses facing AI deployment. Finding talent is especially difficult for early-stage AI users, as successful businesses are most likely to combine hiring methods for finding internal and external candidates with AI expertise.
CIOs also need to ensure that AI specialists are hired and trained during the beginning of a project. A plan will need to be created for developing AI skills that can also be presented for a business case.
Why AI Business Cases Need to Show Measurable Value
Showcasing the business value of a new AI project is essential during the early stages. According to a Gartner survey, 39% of the businesses that successfully created AI projects conducted ROI analysis or used a financial analysis for risk factors. These numbers become essential for buy-in and approval for organizations to highlight how AI projects are superior to conventional technology.
Numerous metrics that extend past simple measurements can help determine the success of using an AI-related project. For example, a company can use AI to enhance the customer count or interaction outcomes with clients for another measure of success.
CIOs need to focus on the value of measuring the success from the initial stages of a new AI project. Always staying proactive in finding data and including a variety of metrics can extend beyond typical financial numbers.
The Value of AI Algorithms for Analyzing Data
AI technology incorporates algorithms to analyze complex data. These interactions between algorithms and data are a critical part of developing an AI business plan. Understanding how to prepare and perfect information for AI has a lasting impact that can be used for creating many models in the future.
Successful uses of artificial intelligence include an extensive infrastructure for data and analytics. A CIO needs to ensure that there is enough supporting data to handle predictions, such as patterns that business leaders can expect to see in the near future. For example, a business that’s making a quarterly prediction should always span several years to highlight quarterly changes.
How to Know When to Buy, Build, or Outsource
The decision to purchase, create, or outsource is highly dependent on the available resources in healthcare or other organizations. The choice between these options will primarily depend on the complexity of each project, as well as the skills of the IT department, the necessary amount of time and urgency for finding a solution, and the budget.
The best path is often determined by the problem an organization is trying to overcome. CIOs can use the following criteria to help determine the best options.
BUILD – Building is a great option for a proposed project if it’s unique to the facility and strong in-house skills are readily available.
BUY – Buying is another choice for specialty applications that can easily be customized to best meet your needs.
OUTSOURCE – Outsourcing is an excellent option if an organization needs to start working on a project immediately but doesn’t have the previous options.
Artificial Intelligence Boom in Healthcare Business
An AI algorithm doesn’t only support the decision-making process, but it can also act autonomously, which is especially beneficial in the healthcare industry. These algorithms are used to analyze large amounts of data, which helps nurses and doctors better serve each patient.
These AI-enabled systems often rely on machine learning technology based on existing data. The growth of AI in healthcare will only continue to expand, as it offers unprecedented insights into providing ongoing care and diagnostics.
CIOs need to work with stakeholders to begin planning for governance demands while implementing AI technology. Staying proactive can play a key role in managing these challenges, while also helping to create trust over time.
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