Carlos Meléndez, an Entrepreneurs' Organization (EO) member in Puerto Rico, is co-founder and COO of Wovenware, an artificial intelligence and software development company which builds smart custom solutions to solve business challenges. We asked Carlos how artificial intelligence will impact business functions in 2019. Here's what he shared:
While there have been advances in artificial intelligence (AI) this year, it's poised to skyrocket in 2019. Companies in multiple industries depend on the technology to gain greater insight, connect with customers and make better-informed business decisions. The technology has been identified as a top strategic initiative for 2019 by leading research firms including IDC, Forrester and Gartner.
- IDC views digital transformation as a business imperative over the next few years, with AI playing a starring role. The firm predicts that AI apps will be an integral part of applications across the enterprise and represent more than $52 billion in global revenue by 2021.
- Gartner sees AI playing a growing role in developing scientific hypotheses based on data and providing intelligence to Internet-of-Things (IoT) devices―such as robots, drones and autonomous vehicles.
- Forrester expects the key focus in 2019 to be on pragmatic AI, as companies implement practical applications for more immediate business benefit.
Each of these firms believes that AI is becoming firmly entrenched in the way we do business and that its role will continue to increase. At our company, we're seeing similar trends and recognize that once businesses get a taste of AI and realize what it can do for them―or see what it's doing for competitors―there's no looking back.
Here are four specific AI trends that we expect to have a significant impact in 2019:
- Image, object and facial recognition. A picture is worth 1,000 words, or more. As data from satellite imagery grows and acquisition prices fall―coupled with the need to identify images for a variety of purposes―so, too, will interest in image recognition, object detection and facial recognition. Image recognition and object detection are increasingly important for security and fraud prevention, as organizations rely on AI apps to find patterns and insights from still images and video. As AI technology evolves to analyze movement, new applications may arise in areas such as healthcare and law enforcement. For example, it could analyze the gait of people with neurological conditions, such as Parkinson's, and how a person's ability to walk may change. Also, when combined with sensor technology and cameras, AI can help identify what someone is doing on the other side of a wall, such as reaching for a weapon.
- Static intelligence is no longer enough. For years, companies have focused on business intelligence for gathering key competitive information from past data and viewing it in dashboards and graphs. However, static information is no longer sufficient for making informed decisions. In today's competitive marketplace, companies require a view of not only yesterday and today's outcomes, but also what's expected to happen in the future so they can anticipate and plan for change. Instead of business intelligence, in 2019 the focus will be on business insights, where companies judge performance on outcome-driven analytics―measuring analytics according to outcomes, and predicting outcomes based on historical data. It will all be about the value that information can create for its users, rather than reports and dashboards.
- "The edge" is the next AI frontier. With the growing use of sensors and other Internet-of-Things (IoT) devices, companies will be gathering information at the edge―meaning at or near the data source rather than in the cloud at a data center. They will focus attention on how to best collect, handle and clean data collected at the edge. Given that algorithms require heavy-duty computing power, the challenge will be how to crunch the data collected at the edge most expediently.
- There still won't be enough data scientists. As demand for AI apps continues to grow, so too will the need for qualified data scientists. AI projects require constant care and feeding from data scientists―it's never one-and-done. In addition to creating algorithms, data scientists need to train AI apps, and continually refine algorithms to reflect new data and insights. Since universities are not graduating enough data scientists to handle current needs, the shortage will only worsen as AI demand grows. Companies will have to rely on partners to either implement self-service AI for general solutions or custom predictive analytics algorithms for more complex problems.
There's no doubt that AI is changing companies and markets as diverse as healthcare, financial services and security. But, as far as we've come, we're just at the starting gate. As the technology becomes more advanced, new needs will emerge, and we'll continue to find ways to combine AI with other innovations, such as IoT. It's an exciting adventure, and the best is yet to come.