Artificial intelligence (AI) is rapidly growing as a vital tool for making business processes more accurate and efficient. Although, only 23% of respondents in a recent study have reported incorporating AI into their processes and service offerings. Slow adaptation of AI may hinder companies from remaining competitive, and has actually shown lower rates of production in comparison with organizations that have implemented AI technologies. Check out our tips below for implementing AI into your operational strategy.
Defining Artificial Intelligence
AI is used as a broad term to define the numerous machine-based tools that can help improve business operations through capabilities like automation and machine learning. AI systems perform human-like tasks that lower the risk of human error. They’re designed to learn, reason, and self correct in order to constantly improve and adjust to a company’s specific needs. The most common AI software, also known as weak/narrow AI, is designed to complete one operational task from data and information provided by an employee. Weak AI is more likely to be used for improving business operations, and is projected to increase productivity levels by 40%.
Steps to Implement AI
Initiating an AI adoption project requires research and insights into competitor experience, as well as an in-depth analysis of an organization’s current operations. Understanding current operations helps executives find pain points that an AI system can improve. Granular research into different AI softwares and technologies is key to tailoring a new system to company goals. Look into competitors’ experience and reviews to get a user perspective on different AI software options, to ensure the one you choose will have a positive impact. Then, implement the top-performing software and monitor it closely to fine tune as you go and yield the best results. Training should also be provided to give employees a firm understanding of how to operate the system and utilize it to its full potential.
The high costs associated with AI software can make it difficult for companies to implement without a planning process that provides the necessary funds. The high cost of these systems is made worth it by not only providing more efficient tools for conducting business, but also through advanced cybersecurity, which is lucrative in the digital age. By 2020, 48% of companies say their budgets for AI in cybersecurity will increase by an average of 29%. Conduct research and forecast up-and-coming AI software trends and suitable options prior to investing. Companies will want the most recent system to ensure their investment lasts long-term and has the ability to evolve and improve.
Examples of Viable Tools
AI tools come in a variety of options, but there are a few that stand out when it comes to maintaining successful business operations. One of the most popular tools in the automation sector of AI. ERP systems (Enterprise Resource Planning systems) help to organize financial, procurement, project, and risk management elements of operations and ensure accurate information is collected to determine next steps. ERP systems make employees’ lives easier, and also increase productivity, organization, and can harness accurate internal business practices.
The next tool is used everyday by professionals in every realm for clear, succinct communication. Email has come a long way with the help of AI automation tools. Spam filters help to eliminate spam emails through learning different patterned elements within the messages so they are blocked from entering the main inbox. Email categorization takes this one step further and allows emails to be organized into seperate folders depending on content. The system learns what is consistently marked as important and condenses the main inbox to only show relevant emails. This reduces time spent messaging and allows communication channels to be organized and more effective.
Ecommerce has boomed in recent years, making the next AI tool lucrative for businesses that conduct online sales. Machine learning plays a role in creating safe and fraud-protected online credit card transactions. False declines are costly, but tools like Square reduce the risk of false declines while also noticing spending patterns of consumers to determine when fraud is actually taking place. Ecommerce’s machine learning capabilities also offer relevant recommendations and search options to buyers to help drive sales.
The Future of AI in Business Operations
Digital transformation has had a major impact on the business world over the years, and artificial intelligence software development has grown at a rapid rate as a result. AI’s place in business operations won’t be going away anytime soon, and is actually paving a new way of conducting business. For this reason, it’s lucrative for companies to remain up-to-date on new trends and software changes. The AI of the future is working towards “Strong AI.” This new version will require less human involvement, further increasing accuracy and removing the chance of bias data. It will be more complex and capable of human-like cognitive actions to create faster, highly-calculated decision making processes, ultimately increasing the pace of operations. Digital testing is key to developing future AI and automation tools, and organizations need to remain connected and well-versed in the advancements in AI technology to ensure they remain competitive and well-equipped to take on the tech-driven future of business.