Intelligent automation can bring myriad benefits to the enterprise, both within IT and across the business. In a recent conversation with Deloitte Consulting LLP Managing Director Brijesh Singh, Nirmal explains. Singh: What are some of the top operational challenges businesses face today? On a macro level, they include inflation and the need to acquire the right skills for competitive success. At the same time, however, the complexity arising from decades' worth of legacy infrastructure presents another set.

We have seen how COVID-19 mounted pressure on businesses to fast-track their digital transformation journeys by months and, in several cases, by years. The arrival of the pandemic made them reconsider technologies they had at their fingertips – artificial intelligence (AI) in particular – and harness them to boost productivity, address supply chain issues, and seamlessly deliver products and services. Organizations have realized the indispensability of integrating AI into their digital strategy and this article will focus on addressing common AI adoption challenges. Artificial Intelligence is a revolutionary technology that saves time, energy, and money. It is no longer confined to science textbooks or science-fiction fantasies; it has countless applications in the real world.

This article is the first in a short series of pieces that will recap each of the day's talks for the benefit of those who weren't able to travel to DC for our first conference. Dr. Sephus came to AWS via a roundabout path, growing up in Mississippi before eventually joining a tech startup called Partpic. When asked, she identified access as the biggest barrier to the greater use of AI/ML--in a lot of ways, it's another wrinkle in the old problem of the digital divide. A core component of being able to utilize most common AI/ML tools is having reliable and fast Internet access, and drawing on experience from her background, Dr. Sephus pointed out that a lack of access to technology in primary schools in poorer areas of the country sets kids on a path away from being able to use the kinds of tools we're talking about. Dr. Sephus said that AWS has been hiring sociologists and psychologists to join its tech teams to figure out ways to tackle the digital divide by meeting people where they are rather than forcing them to come to the technology.

AI is increasingly becoming a business imperative. Nine in 10 Fortune 1000 companies are not only investing in AI, but are increasing those investments, with 92% reporting measurable business benefits from their current AI use -- up from 72% in 2020 and just 28% in 2018, according to a 2022 NewVantage Partners executive survey. Still, only 26% of companies say their AI initiatives have actually moved into widespread production. Cultural barriers, with executives 11 times more likely to say culture is the greatest impediment to AI success than to cite technology limitations as the biggest barrier. And the cultural challenges have actually gotten worse, with 92% of executives citing cultural factors this year vs. 81% in 2018.

O'Reilly just released its annual AI Adoption in the Enterprise survey, and the results are mostly unsurprising. For example, data scientists from organizations with mature artificial intelligence practices tend to turn to scikit-learn, TensorFlow, PyTorch and Keras. Also, supervised learning (82%) and deep learning (67%) were the most popular techniques used by survey respondents, whatever their phase of AI adoption. The biggest barrier to enterprise success with AI is difficulty finding people with the requisite skills. This is the exact same thing that plagues adoption in every technical market as a technology takes off.

Life sciences group the Pistoia Alliance has released a comprehensive survey gauging life-science professionals' views on the implementation of artificial intelligence (AI) and blockchain technology in the life sciences. The findings indicate a high level of interest in AI among respondents, with 57% currently engaging in computational drug repurposing. Also, the findings revealed that awareness of blockchain has increased; 89% now are cognizant of the technology, compared to 82% just three years ago. However, even considering this increase, the survey indicates lack of access to people with relevant blockchain skills remains the biggest barrier to widespread adoption (selected by 30%). Pistoia Alliance consultant Dr. Becky Upton discussed the survey with Outsourcing-Pharma, and how companies might overcome blockchain barriers.

But while these voices are getting louder, they still butt up against systems of power that value profit and the status quo over ensuring that AI is built in a way that isn't harmful to marginalized people and society writ large. In a panel discussion for Fast Company's 2020 Innovation Festival, experts in ethical AI explained what they're up against in trying to change the way that large companies and institutions think about building and deploying AI. For Timnit Gebru, the technical colead of the Ethical Artificial Intelligence Team at Google, one challenge is that she has to work against the incentive structures inherent to capitalism. For publicly traded companies such as Google, constantly increasing profit is the highest good. "You can't set up a system where the only incentive is to make more money and then just assume that people are going to magically be ethical," she said.

This article will explore the biggest barrier to AI adoption in healthcare. Less than 4% of all physician-patient interactions involve AI today; by 2023, one in five interactions will include this strange technology. If those statistics shock you, consider the end goals of most value-based healthcare programmes. Clinical department heads are under increased pressure to reduce costs, enhance the quality of care and improve patient experience -- also known as the "triple aim initiative". In an industry that's known for moving at a snail's pace, artificial intelligence is often viewed as healthcare's magic bullet.

On top of that, 71% of respondents expected AI investment to increase over the coming year. However, the fact remains that there are still significant challenges to companies wishing to adopt smart, cognitive computing processes into their operations. This is borne out by the fact that in the McKinsey survey, just 21% of respondents claimed they had rolled out AI in more than one process. My work brings me into contact with organizations at every stage of their digital transformation and AI adoption process. This gives me insights not only into what is working but why barriers or challenges are discouraging adoption.

Research shows that AI adoption across industry is speeding up – with one report finding that, of over 2,000 organizations surveyed, 47% had implemented it in at least one function, compared to 20% during the previous year. On top of that, 71% of respondents expected AI investment to increase over the coming year. However, the fact remains that there are still significant challenges to companies wishing to adopt smart, cognitive computing processes into their operations. This is borne out by the fact that in the McKinsey survey, just 21% of respondents claimed they had rolled out AI in more than one process. My work brings me into contact with organizations at every stage of their digital transformation and AI adoption process.