For years now AI has been predicted to have the biggest impact of all technological innovations across industries. As a result, futuristic technologies like AI and Big Data are forecasted to break records. That’s because despite their differences, all industries share basic processes like data accumulation, testing, and design among others. As such, AI can automate these processes and make them better and more efficient. Let’s take a look then at how AI will impact major industries this year.
AI’s biggest impact is set to be in the healthcare industry where it’s primed to ironically re-humanize medicine by allowing doctors to focus more on patient care and better patient outcomes rather than paperwork and administrative functions. AI will also be increasingly used as a triage doctor assessing minor illnesses and conditions, allowing doctors to focus on more serious cases. Additionally, the adoption of robotic process automation for functions like revenue cycles, supply chain management, and patient scheduling will also become more accurate and more efficient, as AI helps automate components of these functions.
AI is quickly becoming a key driver behind candidate-job matching as well as automating communications with candidates and HR managers. Forbes explains that AI will be most effective at eliminating human bias and increasing efficiency in candidate assessment and communication. Apart from external candidate matching, AI is increasingly being used internally within organizations to assess internal promotions and leadership candidates. In an article by Marcus on how AI is changing the nature of business, the post outlines how certain businesses utilize algorithms to pinpoint leadership qualities among their employees. That information is then used to identify early-career employees that should be nurtured for leadership positions.
Every company has projects that need planning, managing, and monitoring, however, the existing set of tools that do that are often very complex, and don’t always do enough to warn about potential problems or deficiencies at every level of a project. Managing risk is a critical aspect of project management and AI-powered decision support systems and automation can make projects more successful by reducing costs and mistakes and streamlining processes for better resources management. In fact, we noted how AI will help reduce project manager workload by as much as 20-40% and help gain better insights into project risks.
With the proven success of AI automation and machine learning, AI-driven algorithmic trading accounts for 75% of all financial market volumes. Machine learning is expanding to help major financial institutions cut down time spent on mundane administrative tasks, which can now be completed in a matter of seconds rather than several thousand hours. Machine learning is also used in banking and insurance to improve customer experience through chatbots, predictive analysis for products that customers might need, reducing claim processing times, and helping clients in savings and budgeting better by tracking spending behavior, among many others.