A recent report from Forrester Research, “Predictions 2019: Artificial Intelligence No Pain, No Gain With Enterprise AI,” forecasts major changes in how organizations use artificial intelligence (AI), the rise of new “digital workers,” and increased competition for data professionals with AI skills, among others. According to an article in Analytics Insight, the five top trends Forrester expects to see in 2019, include:
Investment in Information Architecture – According to the report, “The No. 1 challenge for AI adopters is quality data.” To ensure that they have the quality data needed to use AI effectively, Forrester predicts that there will be continued investment in information architecture (IA) to make their data environment “AI-worthy.”
Competition for AI Talent – Another big challenge in AI will be the recruitment and retention of AI talent. According to the report, that talent shortage goes beyond technical experts and data to the need for “industry, social, legal, customer experience, and operational expertise to train, manage, and trust AI systems.” In fact, according to Forrester, some will turn to artificial intelligence for recruitment to help them fill the void.
Convergence with Robotic Process Automation –“The robotic process automation (RPA) momentum started way before AI piqued the interest of enterprises,” the analysts explained. Instead of treating the technologies as distinct, Forrester expects to see an “RPAplus-AI technology innovation chain.” They point out that RPAplus-AI will allow organizations to take “a step further to do such things as create ‘chatbots that boss around RPA bots.’”
Demand for Greater Trust and Explainability – AI solutions are not all equal; some are easily understood and transparent models, while other models are opaque, according to Forrester. With regulations, like GDPR, requiring that “subjects of automated decision-making have the right ‘to obtain an explanation of the decision reached,’” explainability will come to the forefront: “… users will increasingly demand it from their data science counterparts to trust the models that impact customers.”
Looping in Human Expertise – Machine learning and artificial intelligence are great at analysis, predictions, and pattern recognition, but the strength underlying knowledge engineering is human wisdom. “In 2019, enterprise AI mavericks will rediscover knowledge engineering and digital decisioning platforms to extract and encode inferencing rules and build knowledge graphs from their expert employees and customers,” according to the report.
Read the Analytics Insight article here.