Many organizations aspire to automation levels that rival the likes of Amazon, where processes flow seamlessly between people, systems, and devices. A recent Gartner report found businesses are evolving their use of artificial intelligence (AI) as part of their automation strategies, with one third of organizations surveyed applying AI across several business units. If they're honest with themselves, these organizations want automation to achieve some sort of goal -- whether that's improving the customer experience, increasing cost efficiencies, or making life easier for employees. Automation can and should be applied to each of these goals, but it should be done in a fully orchestrated way across the entire organization. Jakob Freund, co-founder and CEO of Camunda, an open-source workflow and decision automation platform, says today, many organizations automate locally -- or within a single team, system, or device.

It's strange that the silly but mostly tolerable horror Choose or Die was an acquisition rather than a homegrown Netflix original given how much it seems algorithmically modeled for the notoriously formula-obsessed platform. It stars Asa Butterfield, an in-house star thanks to the success of Sex Education. It also focuses on a cursed video game, making it a close cousin to the streamer's interactive Black Mirror hit Bandersnatch. It's a film destined to live its days in the "if you like" container. It'll probably fare well there as fans of the above might find just about enough here to play with although they might, like me, be a little surprised at just how nasty this quickie horror is, made with closer attention to the gore quotient than any level of creativity.

Artificial Intelligence and Machine Learning are being used interchangeably as a term across all segments of technological applications. Due to their close relation, AI is often confused with ML but one should not forget the distinction between the two. Out of all the differences, one is surely the biggest – that machine learning is a subset of AI. Technology professionals must understand the trivial difference both possess. Lacking the clarity between AI and ML, professionals as well as their companies may get misguided and eventually lose their relevance in the market with fake or misleading AI solutions. According to an award-winning writer, Stephanie Overby, the most significant misunderstanding is how AI relates to ML.

Of the many technologies with the potential to deliver significant value in the near future, Artificial Intelligence (AI) seems firmly planted atop the list for CIOs. Indeed, nearly all (95 percent) of the CIOs, CTOs, and technology leaders surveyed by IEEE agreed that AI will drive the majority of innovation across almost every industry sector in the next one to five years. "The focus will shift more toward AI-enabled transformation that solves more significant business problems with business-focused solutions," says Jerry Kurtz, executive VP, Insights & Data, at Capgemini Americas. "AI is an enabler and powerful capability, but the time for proofs of concept and science projects is quickly coming to an end. In 2022, expect AI engagements to become larger, more strategically significant, and more mission-critical – with a focus on long-term scalability."

Despite teething problems, artificial intelligence (AI) has become mainstream. In fact, it is more than mainstream. That is to say, no matter how enterprises set up their technology infrastructure, it seems unlikely they will remain competitive without AI. Based on a survey of 5,501 businesses globally, the report shows that one-third of companies are currently using AI in some way, while 43% are exploring it. While recent advances are making AI more accessible than ever, the survey found that a lack of AI skills and increasing data complexity are top challenges.

Pre-pandemic, artificial intelligence was already poised for huge growth in 2020. Back in September 2019, IDC predicted that spending on AI technologies would grow more than two and a half times to $97.9 billion by 2023. Since then, COVID-19 has only increased the potential value of AI to the enterprise. According to McKinsey's State of AI survey published in November 2020, half of respondents say their organizations have adopted AI in at least one function. "As the grip of the pandemic continues to affect the ability of the enterprise to operate, AI in many guises will become increasingly important as businesses seek to understand their COVID- affected data sets and continue to automate day-to-day tasks," says Wayne Butterfield, director of ISG Automation, a unit of global technology research and advisory firm ISG.

Artificial intelligence (AI) capabilities, from machine learning and deep learning to natural language processing (NLP) and computer vision, are rapidly advancing. "Technology has never moved at such pace, meaning the role of the CIO is harder than ever to stay current and up to date with technology overall, so understanding the vast array of AI capabilities is a stretch for most CIOs right now," says Wayne Butterfield, director of cognitive automation and innovation technology research at advisory firm ISG. Naturally, IT leaders are increasingly exploring AI applications in the enterprise. However, AI-enabled initiatives do not necessarily lend themselves to traditional IT approaches. "It is imperative for CIOs to know AI in reasonable depth to understand its realistic and pragmatic adoption," explains Yugal Joshi, vice president of digital, cloud, and application services research for Everest Group.

Artificial intelligence (AI) capabilities, from machine learning and deep learning to natural language processing (NLP) and computer vision, are rapidly advancing. "Technology has never moved at such pace, meaning the role of the CIO is harder than ever to stay current and up to date with technology overall, so understanding the vast array of AI capabilities is a stretch for most CIOs right now," says Wayne Butterfield, director of cognitive automation and innovation technology research and advisory firm ISG. Naturally, IT leaders are increasingly exploring AI applications in the enterprise. However, AI-enabled initiatives do not necessarily lend themselves to traditional IT approaches. "It is imperative for CIOs to know AI in reasonable depth to understand its realistic and pragmatic adoption," explains Yugal Joshi, vice president of digital, cloud, and application services research for Everest Group.

However, for many IT organizations, AI is not just on the IT leader's radar as a business enabler: It's having fundamental impacts on the function itself – from automating some longstanding functions to demanding greater involvement and newer approaches from IT teams. AI is beginning to reshape IT in a number of ways that forward-looking IT leaders will want to follow. Let's consider five worth watching: Tools to automate traditional break-fix and other IT service desk processes are not new, but they're getting significant traction these days, says Wayne Butterfield, director of cognitive automation and innovation at ISG. "An IT Service Desk is as prone to repetition (and therefore automation) as a customer service operation," he says. That's not the only area of hyper AI-enabled automation coming for the IT function. "IT has quickly become not just a partner but a consumer as well, leveraging AI for security and system management to automate processes and move at the speed of an AI-driven enterprise," says Shawn Rogers, vice president of analytic strategy at TIBCO.

Some people use the terms artificial intelligence (AI) and machine learning (ML) interchangeably. The distinction between the two may seem trivial – after all, machine learning is a subset of AI. However, IT leaders and line-of-business leaders need to understand and be able to articulate the differences between AI and ML. As business interest in AI solutions grows, so too does the number of vendors flooding the market with "intelligent" solutions. Without clarity on AI and ML, enterprises can end up pursuing misguided – and ultimately disappointing projects – or falling for fake AI solutions.