At a moment in time when the value of business agility is becoming clearer than ever, a growing range of diverse brands and businesses are prioritizing agility and engaging in digital transformations. Business agility unlocks greater operational flexibility, more nimble and responsive pivots to new processes or priorities, and smarter and more strategic decision-making -- all of which is enormously valuable in an increasingly tech-savvy and competitive professional environment, as discussed in my previous article. One of the most powerful tools that can be deployed to make that transformation successful is artificial intelligence (AI). AI-powered tools and tech form the backbone of systems and solutions that help companies become more agile. What follows is a brief overview of how agile methodologies emerged and why AI delivers such valuable synergies with agile business.

Machine Learning (ML) models built by data scientists represent a small fraction of the components that comprise an enterprise production deployment workflow, as illustrated in Fig 1 [1] below. To operationalize ML models, data scientists are required to work closely with multiple other teams such as business, engineering, and operations. This represents organizational challenges in terms of communication, collaboration, and coordination. The goal of MLOps is to streamline such challenges with well-established practices. Additionally, MLOps brings about agility and speed that is a cornerstone in today's digital world.

Hand an orchestra instruments but no sheet music, and you'll get a cacophony. Create customer and employee experiences without a holistic, user-centered approach and you'll get a technology mishmash that fails to meet user needs. From apps to AR/VR wearables, digital channels are disrupting industries and driving demand from customers and employees for more frictionless, intelligent and personalized experiences. While new innovations can optimize user experience, too often enterprises adopt technologies based on hype instead of taking a deliberate, well-thought approach. This results in busted budgets, undesired services and an inability to meet business objectives.

Advances in cognitive technologies can give marketers the ability to narrowly target consumers. How can CMOs leverage AI to deliver dynamic, contextually relevant content? Over the past decade, with the rise of programmatic media, marketers and their agencies have been moving toward increasingly automated methods of buying advertising to reach high-value target audiences dynamically. With programmatic media buying, machine algorithms buy, serve, and optimize media, often in real time. According to a recent report from eMarketer, marketers in the United States will spend an estimated $46 billion on programmatic advertising this year, and by 2020, 86 percent of all digital display ads will likely be bought via automated channels.

Advances in cognitive technologies can give marketers the ability to narrowly target consumers. How can CMOs leverage AI to deliver dynamic, contextually relevant content? Over the past decade, with the rise of programmatic media, marketers and their agencies have been moving toward increasingly automated methods of buying advertising to reach high-value target audiences dynamically. With programmatic media buying, machine algorithms buy, serve, and optimize media, often in real time. According to a recent report from eMarketer, marketers in the United States will spend an estimated $46 billion on programmatic advertising this year, and by 2020, 86 percent of all digital display ads will likely be bought via automated channels.

Nothing is more annoying to a consumer when browsing online than completely irrelevant content appearing on screen. Interrupting what would be an otherwise seamless, informative browsing experience with unwanted information can trigger an understandably negative reaction among consumers – compromising a brand's reputation in the process. In fact, three quarters (74%) of online consumers get frustrated when confronted with content that has nothing to do with their personal interests. Considering that an estimated 3 billion people now use the internet daily, it's an almost impossible task for brands to take into account individual tastes and preferences. But they need to if they want to engage with today's ever powerful consumer, who engages with a brand at a time, and device of their choice.