Pilot projects of artificial intelligence (AI) technologies proliferated in 2018, as many enterprises tested machine learning (ML) algorithms and an array of automation tools to cement relationships with customers, improve network operations or augment their cybersecurity postures. Encouraged by early results, CIOs are preparing for the next challenge: scaling AI throughout the enterprise. Twenty percent of 1,000 U.S. business executives said their companies plan to implement AI across their enterprise in 2019, according to new research from PricewaterhouseCoopers (PwC). Get the latest insights with our CIO Daily newsletter. Companies are investing more in these emerging technologies, as IDC projects spending on cognitive and AI systems will reach $77.6 billion in 2022 -- more than three times the $24 billion forecast for 2018.

Everybody makes a list of 2019 predictions, but the folks at Deloitte have numbers behind theirs. As one of the world's biggest accounting and financial services firms, Deloitte is able to confidently predict that, for example, the smart speaker market will generate $7 billion in revenues in 2019. Below is Deloitte's 18th annual list of predictions for your enjoyment. "2019 will see massive improvements in a wide range of technologies, pushing once-novel innovations into the mainstreams of our lives and work," said Sandra Shirai, Deloitte's U.S. technology, media, and telecommunications leader, in a statement. "Emerging technologies are blurring traditional industry lines, impacting people and organizations; as a society, we'll be smarter, more productive, and more deeply engaged with the world around us." Deloitte said in its forecast that it expects 164 million smart speakers to sell in 2019 at an average price of $43.

It's been a while since businesses have been debating over investment into data and analytics. Some people have already done it and it is working out. We are over and above the apprehensions of whether Data investments work or not, now, the questions is how soon you can make it work. It has to be strategy first and a top down push on getting the data investments to execution and results. It is a herculean task but by now there are already best practices and open source tools to help adopt the data solutions.

Artificial intelligence and machine learning became popular buzzwords in 2018, thanks in large part to companies adopting the emerging technologies to expand their businesses and acquire new customers. AI-based technologies helped companies add new revenue streams and optimise current ones. According to an analysis by professional services firm PwC, technological disruption has also impacted the mergers and acquisitions (M&A) or investment strategies of large corporations. "With larger corporations looking to adapt to technological advancements and revamp their business models, 2018 has seen a number of acquisitions in the new technology space," said Sanjeev Krishan, partner and leader, private equity and deals, PwC India. "Relevance has become a key element for the survival of any business, and this has made technology expertise a requirement to achieve a competitive advantage in the current market," he added.

There are certainly of theories floating about, but consulting firm PwC predicts that organizations that focus on six key areas will become AI leaders. Pressure will increase to scale up AI in 2019 to enhance decision-making and provide forward-looking intelligence for users in every department and function. Having the right AI governance model enables companies to develop use cases that create quick wins. AI is being democratized, but is still so complex that even trained business specialists can make mistakes. Organizations need to develop the right mix of citizen users, citizen developers, and data scientists, and give them the tools, training, and incentives to help them work collaboratively. Customers, employees, boards, regulators, and corporate partners are wondering if they can trust AI.

As Kirk Borne of Booz Allen Hamilton explains, AI-as-a-service offerings can be transformative for both businesses and employees in serving customers. If you are inclined to think providing excellent service to your customers isn't rocket science, think again. In today's digital topography, big data reigns supreme, and the ability to intelligently deploy technologies that can make sense of the information out there is the key to competitive advantage. Data science as a discipline is moving beyond the classroom and into the boardroom, as more and more executives and directors are realizing the tremendous opportunities it opens to their organizations. To discuss some of the business applications for data science and artificial intelligence, we spoke with Dr. Kirk Borne, Principal Data Scientist and Executive Advisor at management and technology consulting firm Booz Allen Hamilton.

The manufacturing industry is experiencing a growing talent shortage. Data from Deloitte shows that by 2025 the manufacturing skills gap will widen, creating the need for 3.4 million skilled workers, with 2 million of those roles going unfulfilled. Driving this void will be the 2.7 million workers who will retire or leave the industry by 2025, in addition to the roughly 700,000 jobs that will be created by growth within the industry. There still exists a widespread misperception that automation and robots will put manufacturing jobs at risk. This is not the case.

Twenty percent of executives at U.S. companies with artificial intelligence initiatives report that they will roll out AI across their business this year, according to PwC's 2019 AI Predictions report. These companies expect their AI investment, which is often part of intelligent automation initiatives, to go beyond improving productivity and cutting costs. They see AI as a path to growing profits and revenue in 2019. However, the executives in the survey said that there are challenges, such as training employees to use AI systems, and security threats remain a concern. Success in leveraging AI will be built on strategies for the organization and the workforce, for creating responsible AI and AI-ready data, for reinventing the business, and for integrating AI with other technologies.

Most executives know that artificial intelligence (AI) has the power to change almost everything about the way they do business -- and could contribute up to $15.7 trillion to the global economy by 2030. But what many business leaders don't know is how to deploy AI, not just in a pilot here or there, but throughout the organization, where it can create maximum value. The "how" is the sticking point with any emerging technology, and AI is no exception. How do you define your AI strategy? How do you find AI-literate workers or train existing staff?

Headlines about automation and workforce disruption are good for thinking about the future, but what is today's reality? From our latest AI trends research, we know that business leaders aren't adopting technology for technology's sake. Instead, they're acknowledging the now: AI may be the future, but what can automation and AI do for me today? Does the organization want to automate billing, general accounting and budgeting, and compliance functions? Automation and AI will likely be a part of the solution in all of these areas, and workers should not fear it.