This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review's editorial staff. AI-enabled fraud and the coming impact of quantum computing are redefining digital-asset security, putting pressure on owners and service providers to act now. Cryptocurrency thieves are getting creative. Taking advantage of the desire to learn more about crypto and banking on the digital assets' reputation as a way to get rich quick, AI-generated video tutorials are touting ways of make money from crypto-trading arbitrage -- purportedly teaching viewers how to create maximal extractable value from trades using smart contracts.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review's editorial staff. How ambient AI assistants are supporting clinicians to save time, reduce burnout, and enhance treatment, restoring the doctor-patient experience. For many clinicians, administration is a whole job on its own. From examination findings to proposed treatments, test results, and patient education, clinicians must maintain accurate, clear, and timely clinical records every step of the way.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review's editorial staff. Modern integration platforms are helping enterprises streamline fragmented IT environments and prepare their data pipelines for AI-driven transformation. Enterprise IT ecosystems are often akin to sprawling metropolises--multi-layered environments where aging infrastructure intersects with sleek new technologies against a backdrop of constantly ballooning traffic. Similarly to how driving through a centuries-old city that's been retrofitted for automobiles and skyscrapers can cause gridlock, enterprise IT systems frequently experience data bottlenecks.

Few technological advances have generated as much excitement as AI. In particular, generative AI seems to have taken business discourse to a fever pitch. Many manufacturing leaders express optimism: Research conducted by MIT Technology Review Insights found ambitions for AI development to be stronger in manufacturing than in most other sectors. They see AI's utility in enhancing product and process innovation, reducing cycle time, wringing ever more efficiency from operations and assets, improving maintenance, and strengthening security, while reducing carbon emissions. Some manufacturers that have invested to develop AI capabilities are still striving to achieve their objectives.

Along with poor data quality, these issues combine to deprive organizations' data platforms--and the machine learning and analytics models they support--of the speed and scale needed to deliver the desired business results. To understand how data management and the technologies it relies on are evolving amid such challenges, MIT Technology Review Insights surveyed 351 CDOs, chief analytics officers, chief information officers (CIOs), chief technology officers (CTOs), and other senior technology leaders. They are succeeding thanks to their attention to the foundations of sound data management and architecture, which enable them to "democratize" data and derive value from machine learning. Pushing these to the edge with advanced data technologies will help end-users to make more informed business decisions -- the hallmarks of a strong data culture. Organizations' top data priorities over the next two years fall into three areas, all supported by wider adoption of cloud platforms: improving data management, enhancing data analytics and ML, and expanding the use of all types of enterprise data, including streaming and unstructured data.

The names of many of the new companies and technologies created to combat the effects of climate change on marine ecosystems can evoke thrilling acts of derring-do on the high seas. WaveKiller uses compressed air systems to create "walls" of bubbles up to 50 feet thick, to guard against erosion and contain waste and oil spills. The Inceptor is a solar-powered barge deployed by the Dutch nongovernmental organization Ocean Cleanup along rivers in Southeast Asia to gather tons of waste before it hits the sea. Saildrone and WasteShark build and deploy fleets of autonomous drones to ply the oceans, gathering meteorological and marine data in the former case and trash in the latter. This sample of (often menacingly-named) technologies represents the increasingly diverse approaches to combat marine degradation--diversity which is desperately needed, as climate change wages war on the health of the world's oceans on many different fronts.

Successful data strategies are built on a foundation of meticulous data management, creating enterprise architectures that "democratize" data access and usage, yielding measurable results from machine learning platforms. The reality, according to an examination of the emerging "AI organization," is that few data-driven organizations are able to deliver on their data strategy. A survey commissioned by Databricks and conducted by MIT Technology Review Insights found that a mere 13 percent of those polled actually achieve measurable business results. MIT Technology Review Insights said it polled 351 CDOs, chief analytics officers as well as CIOs, CTOs and senior technology executives. It also interviewed several other senior technology leaders.

In 2008, the UK published its first national risk register, allowing a public sense of the national security priorities for civil emergencies. The report measured risks along two dimensions--relative impact and relative likelihood--with the possibility of a pandemic influence topping the list. A year later the world saw the swine flu pandemic, causing hundreds of thousands of deaths. While the UK saw hundreds of thousands of cases, they saw relatively few deaths. From the perspective of governments, pandemics are not black swans. The issue is not whether a country foresees a pandemic and prepares accordingly, it's whether the systems in place can function under the level of stress resulting from a pandemic.

For some time, leaders of technology-enabled health-care institutions--and today, that means practically all health-care institutions--have been anticipating the potential impact that artificial intelligence (AI) will have on the performance and efficiency of their operations and their talent. But in reality many, if not most, have already been reaping the benefits of AI tools, which are improving many activities in health-care institutions, from enhancing oncological diagnosis accuracy to reducing time spent scheduling patient visits. In a survey conducted by MIT Technology Review Insights, in association with GE Healthcare, more than 82% of health-care business leaders report that their AI deployments have already created workflow improvements in their operational and administrative activities--giving clinicians time back to work with their patients more closely, and with more insight. This report, alongside an interactive experience on technologyreview.com, is the conclusion of our survey of more than 900 health-care professionals in the US and the UK.

CHICAGO & LONDON--(BUSINESS WIRE)--Artificial Intelligence (AI) is widely expected to drive important benefits across the health system, from increasing efficiency to improving patient outcomes, but it also may be key to making healthcare more human. Benefits range from increasing the amount of time clinicians can spend with patients and on cross-care team collaboration to enhancing the ability to deliver preventative care. According to a new study of more than 900 healthcare professionals in the U.S. and U.K. conducted by MIT Technology Review Insights with GE Healthcare, nearly half of medical professionals surveyed said AI is already increasing their ability to spend time with and provide care to patients. Additionally, more than 78 percent of healthcare business leaders who reported they have deployed AI in their operations also reported that AI has helped drive workflow improvements, streamlining operational and administrative activities and delivering significant efficiencies toward transforming the future of healthcare. "Of any industry, AI could have the most profound benefits on human lives if we can effectively harness it across the healthcare system," said Kieran Murphy, President and CEO, GE Healthcare.