Artificial Intelligence & Machine Learning

We know that use cases for AI and machine learning get very industry-specific very quickly. So we thought it would be interesting to look at which use cases in which industries might get more traction, and which will see less adoption during the COVID-19 pandemic, and what comes after.

We know that use cases for AI and machine learning get very industry-specific very quickly. So we thought it would be interesting to look at which use cases in which industries might get more traction, and which will see less adoption during the COVID-19 pandemic, and what comes after.

How can these technologies contribute to response, both globally and locally – and what privacy concerns could they raise, both now and in the months to follow?

It is becoming increasingly clear that new approaches to data processing, data management and analytics not only are key to differentiating the most data-driven companies from the least data-driven, but are also fundamental to the ability to execute digital transformation strategies. As we look ahead to 2020, we outline six key data trends that will enable successful digital transformation in the years ahead.

Until now, many adoptees were more focused on rolling out AI applications into production and less concerned with developing standards and procedures to ensure the technology is safe, manageable, robust, explainable and sustainable. As these downstream challenges become more prevalent in 2020, we expect the industry to formalize frameworks, products and services around these key areas.

While the gains in efficiency and automation provided by AI and machine learning are transforming a wide swath of business processes, the proliferation of enterprise AI is itself driving changes in enterprise IT infrastructure.

According to new data from 451 Research's VotE: AI and Machine Learning survey, less than half of early adopters have defined key performance indicators (KPIs) around their AI and machine learning initiatives, although the vast majority plan to do so within a year.

AI and machine learning adoption is not monolithic. In fact, according to new data from 451 Research's VotE: AI and Machine Learning survey, enterprise adoption strategies segment into four categories.

The initial wave of AI adoption has centered on making legacy systems and processes more intelligent. Embedding machine learning into customer service and support, BI, customer experience, sales, marketing and security applications can make these processes more automated and efficient.

The Voice of the Enterprise (VotE) quarterly surveys focus on major themes, and 451 Research clients can access the service in ways that make sense for their business. These themes now include AI & Machine Learning.

For a comprehensive look at machine learning – covering everything from the technological underpinnings to the financial outcomes in the sector – watch 451 Research’s Research Vice Presidents Brenon Daly and Nick Patience discuss the machine learning market including how some key tech acquirers are participating in the rapidly emerging market.

Artificial intelligence and machine learning are set to revolutionize not only the software industry, but also the way we live, work, learn and play. We examine the use cases and technologies setting the pace in this rapidly evolving space.