It's that time of year again to gaze into the crystal ball. With so much hype around the promise of machine learning and AI, below are some ideas from various industry executives about what impact these technologies will be making on IT business and our lives in general.

Alan Conboy, office of the CTO, Scale Computing

"In 2019 Artificial Intelligence (AI) and Machine Learning (ML) will nearly reach its full potential by connecting and processing data faster over a global distribution of edge computing platforms. AI and ML insights have always been available, but possibly leveraged a bit slower than needed over cloud platforms or traditional data centers. Now we can move the compute and storage capabilities closer to where data is retrieved and processed, enabling companies, organizations and government agencies to make wiser and faster decisions. We're already seeing this in the way airlines build and service airplanes, government defense agencies respond to hackers and how personal assistants make recommendations for future online purchases. This year, thanks to AI and ML, someone will finally know if that special someone really wants a fruitcake or power washer."

Stephen Gailey, solutions architect, Exabeam

"2019 seems as if it will be the year of analytics, machine learning and AI.  These tools are already available, though their take up has often been delayed by a failure to match these new capabilities with appropriate new workflows and SOC practices.  Next year should see some of the pretenders - those claiming to use these techniques but actually using last generation's correlation and alert techniques in disguise - fall away, allowing the real innovators in this field to begin to dominate.  This is likely to lead to some acquisitions, as the large incumbents, who have struggled to develop this technology, seek to buy it instead. 2019 is the year to invest in machine learning security start-ups demonstrating real capabilities."

Scott Parker, director of product marketing, Sinequa

"Some existing applications that we may see more than others in 2019 will be chatbots and increasingly autonomous vehicles. The improvement in chatbot AI capabilities, will create an opportunity for innovative customer service groups to step up in 2019 over competitors. 2019 will also be a big year for autonomous driving initiatives to leverage empirical data with continuously improving algorithms and hardware processing power."

Setu Kulkarni, vice president of corporate strategy, WhiteHat Security

"As AI and ML become mainstream, a new breed of security data scientists will emerge in 2019: AI and ML techniques are data dependent. Preparing, processing, and interpreting data require data scientists to be polymath. They need to know computer science, data science, and above all, need to have domain expertise to be able to tell bad data from good data and bad results from good results. What we have already begun seeing is the need for security experts who understand data science and computer science to be able to first make sense of the security data available to us today. Once this data is prepared, processed and interpreted, it can then be used by AI and ML techniques to automate security in real time."

Bob Davis, CMO, Plutora

"In software development, the big story in 2019 will be machine learning and AI. In the coming year, the quality of software will be as much about what machine learning and AI can accomplish as anything else. In the past, delivery processes have been designed to be lean and reduce or eliminate waste but to me, that's an outdated, glass-half-empty way of viewing the process. This year, if we want to fully leverage these two technologies, we need to understand that the opposite of waste is value and take the glass-half-full view that becoming more efficient means increasing value, rather than reducing waste.

Once that viewpoint becomes ingrained in our M.O., we'll be able to set our sights on getting better through continuous improvement, being quicker to react and anticipating customer's needs. As we further integrate and take advantage of machine learning and AI, however, we'll realize that improving value requires predictive analytics. Predictive analytics allow simulations of the delivery pipeline based on parameters and options available so you don't have to thrash the organization to find the path to improvement. You'll be able to improve virtually, learn lessons through simulations and, when ready, implement new releases that you can be convinced will work.

Progressive organizations, in 2019, will be proactive through simulation. If they can simulate improvements to the pipeline, the will continuously improve faster."