One in five enterprises sees modernizing its data infrastructure for AI as the top AI initiative to ... [ ] gain a competitive edge today. These and many other fascinating insights are from Deloitte Insights' Survey: State of AI in the Enterprise, Third Edition: Thriving in the Era of Pervasive AI. A PDF of the study is available for download here (28 pp., PDF, no opt-in). Deloitte surveyed 2,737 IT and line-of-business executives between October and December 2019 from nine countries. To qualify for the study, all responding executives needed to have experience evaluating, budgeting for and implementing AI investments.

Nearly all asset managers using artificial intelligence-based technology in their pre-investment phase said it helped them to generate alpha. A survey from Deloitte Center for Financial Services found that 85% of respondents said using AI-based solutions in the pre-investment stage helped them generate returns. For example, using natural language processing and generation saves time on data collection and allows analysts to focus on interpreting the data. In addition three quarters, 71%, of respondents said they would increase their budget for alpha-generating technologies such as artificial intelligence over the next 12–18 months. Financial services have reached an inflection point, driven by technology, talent, regulation and purpose.

AI and machine learning are breaking down silos that hold Financial Services firms back from ... [ ] delivering more valuable insights to customers. AI and machine learning are reordering the Financial Services landscape, navigating an entire industry back to its customers. Fintech is forecast to achieve a compound annual growth rate (CAGR) of 25% through 2022, reaching a market value of $309B. The broader financial services market expected to reach $26.5T by 2022, achieving a 6% CAGR. AI and machine learning are the catalysts that every organization in Financial Services is either adopting or evaluating to break down silos, automate processes and remove barriers between themselves and their customers.

The future of health is expected to be driven by an omnipresent, proactive, and integrated system of health and well-being where transformational technologies (e.g., artificial intelligence, quantum computing, cloud storage, augmented and virtual reality, and so on) are poised to play a huge role. When it comes to medtech, we expect medical devices to meld hardware and software to allow customers to diagnose and perhaps even treat medical conditions at home. And as health care's focus moves toward prevention instead of treatment, the future devices may alert care teams about potential health issues before they become symptomatic through always-on sensors. As medtech companies' business models are likely to change dramatically, they should consider collaborating with technology companies to address the increasingly changing needs and expectations of consumers. To find out what the medtech company of the future will look like (and more), the Deloitte Center for Health Solutions conducted a crowdsourcing simulation with experts across digital health startups, medtech companies, technology companies, health plans, health systems, and research institutions.

The Internet of Things (IoT) is getting smarter: companies are incorporating Artificial Intelligence (AI) -- in particular, machine learning -- into their IoT applications and seeing capabilities grow, including improving operational efficiency and helping avoid unplanned downtime. Companies are finding that machine learning can have significant advantages over traditional business intelligence tools for analyzing IoT data. With the above capabilities enabled by AI, its powerful combination with IoT technology is helping companies avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management. In a number of sectors, unplanned downtime resulting from equipment breakdown can cause heavy losses. And "predictive maintenance" can greatly help mitigate or reduce such losses.

As 2017 is coming to its end, it's an opportune time to look at what C-suite executives will be turning their attention to in the coming months. Deloitte's recently released Technology, Media and Telecommunications (TMT) Predictions, provides insights into key technology trends on the consumer and business front. While some may come as no surprise, these developments could have a significant impact on enterprise strategies. Machine learning will intensify for businesses across the board. Medium and large-sized enterprises surveyed say they will double the number of implementations and pilot projects using machine learning technology in 2018, and then double it again by 2020.