Blog: Building a Modern Enterprise with Artificial Intelligence – CIO
For today’s enterprises, artificial intelligence isn’t just a good idea. It’s becoming a new imperative. To stay competitive and relevant in their industries, enterprises increasingly need to become AI-driven. AI is a new key to improving business processes, making better decisions, monetizing data, increasing security and more.
The growing importance of AI in the enterprise is a point that industry observers now emphasize. Just consider this view from the global consulting firm Deloitte: “As AI technologies standardize across industries, becoming an AI-fueled organization will likely be table stakes for survival. And that means rethinking the way humans and machines interact within working environments.”1
Leaders of forward-looking enterprises are saying many of the same things, as they are investing in AI. As Michael Dell, founder and CEO of Dell Technologies, points out in an online webinar, “Seven of the 10 most valuable public companies in the world are using deep learning and AI at the heart of their operations.” He notes that, in this new era, organizations are reimagining every aspect of their operations, their businesses, their products and their services to deepen customer relationships, to grow new capabilities and to design better products.2
These are all among the benefits of an AI-driven enterprise. Enterprises are now using AI to enable predictive maintenance of machinery, to optimize logistics and supply chains, to streamline customer interactions in call centers, to drive higher sales with personalized product recommendations, and to create new products and services. The possibilities created by AI systems go on and on.
We now have all the components for AI
For organizations that recognize the need to become AI-driven, there’s good news: All the key pieces of the puzzle are now in place. These include an abundance of affordable compute and storage, faster networks, massive amounts of data, new algorithms, and pre-validated solutions for machine and deep learning. Put it all together, and AI becomes more accessible than ever before, even to small and midsize businesses.
In an interesting twist that comes with the age of AI, the deluge of data from the Internet of Things (IoT), social media, enterprises systems and other channels is increasingly seen less as an IT problem and more as a business opportunity. That’s because massive amounts of data are essential for training the machine learning and deep learning applications that are at the heart of AI solutions.
This is a point that a Gartner analyst calls out in a recent look at the top data and analytics trends for 2019. “The very challenge created by digital disruption — too much data — has also created an unprecedented opportunity,” notes Donald Feinberg, vice president and distinguished analyst at Gartner. “The vast amount of data, together with increasingly powerful processing capabilities enabled by the cloud, means it is now possible to train and execute algorithms at the large scale necessary to finally realize the full potential of AI.”3
Overcoming barrier in the road to AI
While it is a huge step forward to finally have all the components in place, AI initiatives still pose significant challenges for organizations that are working to become AI-driven. For example, organizations tend to struggle with issues related to data quality, governance and availability. Many lack in-house data-science skills and have trouble recruiting data scientists, who are in short supply. And the implementation of AI in the enterprise often requires the rethinking of well-ingrained processes.
None of these and other such challenges are insurmountable. Today, there is a broad ecosystem working to knock down all of the barriers in the road to AI.
For example, various technology companies now offer automated machine learning capabilities that help people with little to no data science expertise build and deploy machine learning solutions. This same ecosystem is making AI development platforms easier to deploy and use. That’s the case with Nauta, an Intel-initiated data science workbench designed to run deep learning models in container environments on systems based on Intel® Xeon® Scalable Processors.
There also are new off-the-self solutions, such as Dell EMC Ready Solutions for Al, that simplify and speed AI deployments. These solutions simplify the path to AI applications by delivering fully featured machine learning and deep learning platforms, so data scientists can spend their time building models instead of building infrastructure.
With solutions like these making AI systems easier all the way around, organizations can now shift the focus to bigger-picture issues. What organizations need most is a vision for using AI throughout the enterprise, an AI strategy endorsed by the C-suite and a stepwise action plan for realizing the vision.
To learn more
To learn more about technologies for AI in the enterprise, explore Dell EMC solutions for artificial intelligence.
1 Deloitte, “AI-fueled organizations: Reaching AI’s full potential in the enterprise,” January 16, 2019.
2 Michael Dell, Dell Technologies webinar, “How Dell Technologies enables the future of AI/ML to Unlock the Power of Data,” November 14, 2018.
3 Gartner news release, “Gartner Identifies Top 10 Data and Analytics Technology Trends for 2019,” February 18, 2019.