Tech behemoths repeatedly have called the race: Artificial intelligence (AI) has officially entered the mainstream, and it's done so in a resounding fashion. AI is, quite literally, everywhere. A PwC survey found that more than half of respondents accelerated AI efforts due to COVID, with nearly 90 percent indicating they view AI as a mainstream technology. Similarly, an IDC report shows that AI system spending will grow by 140 percent by 2025 - on top of the already massive amount of growth the technology already has experienced. Mainstream indeed, and of course when your favorite technology - like your favorite band - goes mainstream, there's good and bad that comes along with it.

Mass migration to the cloud, ethics in business processes, and consumer concern over data privacy and security, whether it be in an election or a breach caused by ransomware, have become a focus for most major enterprises. To continue finding success in the "new normal," companies will need to adapt to its new demands with foresight and agility. They need to prepare to meet the growing demand for IT, consumer concerns over data rights, and integrating ethical AI into their product development. As demand for IT grows in a COVID world, self-serve analytics will accelerate. As the pandemic continues in 2021, companies will look to further reduce dependencies on IT functions with self-serve analytics.

AI and cloud environment adoption has changed the game for IT over the past decade. These technologies have opened the door for businesses to create compelling digital experiences. But they have also come with a cost, introducing new levels of complexity into enterprise technology stacks. Now it's more difficult than ever to understand your IT environment, let alone identify and resolve any problems that may be occurring in that environment. That's why, as 2020 and a new decade get under way, I'm predicting that these three trends will define how enterprises finally rein in IT complexity.

AI in the enterprise has proven to be a slow-growth and experimental journey for companies that don't fall into the category of massive tech giants and Fortune 500 businesses. In the early stages, companies have toyed with machine learning-its capabilities and how they can apply it to their business. This stage is dependent on digital readiness, the skills in an organization and the business problem that needs to be solved. However, many companies have become overwhelmed and distracted with the constant buzz around the latest advancements in machine learning algorithms; leaving missed opportunities for right-sized, tangible implementations and progress. In 2020, AI will be found in an expanded pool of business roles, use cases and companies of all sizes.

Artificial intelligence has no doubt had a huge impact on business and society as a whole. As 2019 comes to a close, let's take a look at the new developments in automation, hardware, tools, model development, and more that will shape (or accelerate) AI in 2020. Signs point toward an acceleration of AI adoption. We see the AI space poised for an acceleration in adoption, driven by more sophisticated AI models being put in production, specialized hardware that increases AI's capacity to provide quicker results based on larger datasets, simplified tools that democratize access to the entire AI stack, small tools that enables AI on nearly any device, and cloud access to AI tools that allow access to AI resources from anywhere. Integrating data from many sources, complex business and logic challenges, and competitive incentives to make data more useful all combine to elevate AI and automation technologies from optional to required.

With more and more companies looking to digitally transform their business, 2020 will lead to the rise of citizen data scientists, citizen developers and more. For example, democratizing software would enable developers to generate data models without having the skills of a data scientist. They would instead rely on AI and ML-driven development and predictive models to generate code and automate testing. Recent advancements in low-code and no-code software design have given rise to the concept of the "citizen developer." Today, an increasing number of developers are using low-code platforms to build custom software on top of pre-built app templates.

AI and ML will become truly transformational in our everyday lives in 2020. Aiding their rise will be the ever-growing cloud ecosystem and the move of ever more business-critical workloads feeding seemingly unstoppable growth. We'll also see changes in the global pecking order among the big players, as Chinese companies reorder the hierarchy in high growth markets. Change may be constant, but we believe 2020 is going to be a uniquely fascinating year! Operational workloads move to cloud and embrace AI and ML: Businesses will expedite the move of their operational data away from legacy providers like Oracle and SAP to cloud-native database management solutions.

As I look back at 2019 and the changes that shaped the IT landscape this year, we saw more widespread adoption of solutions that both run on and regurgitate datasets in efforts to improve business intelligence. We are increasingly seeing the role of data in enabling futuristic technologies like data analytics, machine learning, Artificial Intelligence (AI) and the Internet of Things (IoT). With 2020 on the horizon, everything is trending toward how and why companies use their data to serve consumers, make decisions for competitiveness, and iterate operations to improve profitability. For this reason, I think that one of the biggest challenges of 2020 will be how companies can secure a reliable storage, deployment and usage posture for their datasets. Datasets need to move around fast during usage and deployment stages, but also securely.

If you're a tiny bit freaked out by the enormous potential of AI and blockchain, you're not the only one. When Dolly the sheep was cloned in the 90s, a pertinent question arose. Just because we can, does it mean we should? Just because AI and blockchain technologies combined may stop crimes before they happen, replace human jobs with robots, and assign every "thing" in the stratosphere an identity-does it mean they should? Are AI and blockchain combined super cool or a little creepy?

Hardware is far from dead - it's rapidly evolving. As the future of data centers become increasingly tied to software and cloud offerings, companies that service hardware are innovating to meet the new needs of their clients. These shifts in the industry's landscape create both tremendous opportunity and emerging risk. To find out more, I spoke with Chris Adams, President and Chief Operating Officer at Park Place Technologies, to talk about the role of hardware for the cloud, artificial intelligence and more. VMblog: First, who is Park Place Technologies, and what does their history entail?