Simon Kim is the CEO and founder of Glassdome.
Most businesses are already using AI, and there are good reasons for this.
AI can make an enormous difference in any industry. In call centers, for example, AI helps agents quickly solve customers’ problems and provide better service. On farms, AI can lead to greater crop yields and fewer pests. AI can lead to more efficient and environmentally friendly operations on factory floors.
All of these breakthroughs require one thing: quality data.
AI relies on quality data—as much of it as possible—to produce meaningful results. Just like humans need to eat nutritious food to thrive, AI needs to ingest and use quality data to excel. Using AI technology without quality data almost guarantees businesses won’t get the most out of it. Data is much like a home’s foundation: AI operates on shaky ground without it.
It takes time and effort to get quality data, but AI can find patterns and actionable information sooner when it uses suitable data, such as data that is trapped inside antiquated legacy computer systems or, for manufacturers, trapped inside a machine on a factory floor. Even after finding this data, it must be organized in a central location. Businesses must also resist the temptation to coast by using obsolete data.
How Quality Data And AI Can Transform Organizations
By working to get the best data for their AI technology, the results can be transformative. Here are four examples:
1. Cost Savings: When AI works with questionable data, the best it can do is guess. An AI system working with weak data isn’t much different than a hunch. When supplied with accurate data, though, AI can better predict crucial parts of the business, such as costs, yields and output. Manufacturers, service operations and marketers already see cost reductions due to AI. A 2023 Statista study found that roughly 4% of companies cut costs by 20%, and 28% lowered their costs by at least 10% after adopting AI.
2. Better Training And Workforce Utilization: Turnover is a consistent problem in almost every industry, particularly manufacturing, service jobs and call centers. When AI receives quality data, it can operate as a business’s copilot. AI can identify best practices and find stumbling blocks for new employees. This can speed up onboarding and help produce quicker results. When people inevitably leave these positions, their replacements can get up to speed and contribute—often in days.
3. Minimizing Risks: In the past, businesses relied on manpower to help companies analyze compliance risks. AI does a better job, particularly when supplied with good data. AI can use machine learning and natural language processes to identify potential compliance risks and provide actionable insights to mitigate risks. This helps companies avoid legal or regulatory issues and stay current with codes and guidelines. AI does this work via algorithms that can quickly scan through contracts, policies and other legal documents to identify compliance issues.
4. Improving The Environment: A company that uses AI and supplies it with quality data is well on its way to becoming a sustainable, green business. When AI has the right data, it can look for ways to help enterprises significantly reduce energy spending, use fewer raw materials and source supplies from sustainable companies. Put together, these steps can greatly reduce a company’s environmental footprint.
How Do Companies Obtain Higher Quality Data?
There are several actions businesses can take right away to improve the quality of their data, including:
1. Invest in infrastructure. Companies that use outdated software or legacy systems often need help obtaining quality data. Companies should ensure they have the best possible technology within their budget and look for ways to upgrade antiquated technology.
2. Use a centralized, well-maintained platform. One of the biggest problems companies have—even with robust tech—is that data is spread out in different locations. Instead, companies should use a single platform as a clearinghouse and repository for all crucial data.
3. Find hidden data. Companies often own machines that hold data that could be crunched and used to build more efficient businesses. Manufacturers, for example, use thousands of machines that contain invaluable data that could help them run more efficient and green businesses. Companies should look around and identify places where data might be hiding; even old legacy equipment data can be unlocked by the right partner or software.
Although there has been a fair amount of fear-mongering, the reality is that AI offers a path to building better and healthier companies.
For companies to get there, their priority should be ensuring they have access to the best data possible. AI can only work at its best and help companies become more successful and purpose-minded when it starts with quality data.
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