Wovenware predicts 2018 will be the year that AI moves from a long-range goal for companies, to an immediate priority across industries, such as manufacturing, government, insurance and financial services.
“During 2017, companies were becoming more familiar with AI, exploring its possibilities and how it could fit into their organizations,” said Carlos Melendez, COO, Wovenware. “In 2018, we expect this planning to be put into action, as more and more companies incorporate data-driven insights from deep-learning algorithms, chatbots, and machine learning tools into their business applications. This will not only help companies improve customer service, generate greater efficiencies and predict outcomes – but they will also benefit from using AI to read facial expressions, understand human emotions and identify patterns of behavior from huge amounts of structured and unstructured data. ”
According to Forrester Research in a recent report, 70 percent of enterprises expect to implement AI over the next 12 months , up from 51 percent in 2017. As many companies learned in 2017, AI requires a complete transformation in how businesses operate, interact with customers and structure their human assets, and it’s not something that is quick and easy to do on their own. Despite this, companies are moving full steam ahead in 2018.
Key market trends are driving the implementation of AI into all facets of an organization:
- A focus on the end-user experience. With advances in cloud, mobile and social technologies, consumers and business end-users alike, not only expect a fast and easy digital experience, but they expect businesses to understand their specific needs and preferences. AI is helping companies meet these needs, with chatbots that immediately respond to and understand specific customers 24/7, and can tailor products and services that reflect this understanding.
- The IoT explosion. While sensors that are attached to products out in the field, and communicating key information back to computers are bringing new insights into product design and development, they are also adding more data to data-deluged organizations. Deep learning tools are enabling AI algorithms to make sense of this data and identify patterns that would be impossible with the human eye.
- Concerns about a changing workforce. As robotic process automation and other technologies have enabled robots to perform many predictable, process-driven tasks, there has been growing concern about technology replacing workers. But while AI may replace jobs, it also provides an opportunity for many workers to transform their roles to more strategic ones to keep pace with a constantly evolving, competitive marketplace. Gartner recently predicted that by 2021, 40 percent of IT staff will be versatilists holding multiple roles, most of which will be business- rather than technology-related.
- Traction of big data and cloud. In 2017 more companies moved directly to the cloud, from on-pemise or hybrid environments. Adoption of cloud computing, coupled with complex sources of big data, is supporting the growth of AI. In a synergistic relationship, the cloud helps AI gather the information it needs to learn, while AI provides the information the feeds the cloud more sources of data.
“As the adoption of AI becomes mainstream in 2018, a key challenge will be the shortage of qualified data scientists,” added Melendez. “AI requires expertise in statistics and analytics, combined with more analytical skills in translating that data to provide strategic business value. While universities have recognized this growing profession and adopted relevant courses of studies, it will take time to train rising professionals, and the shortage should remain for the next few years.”