Artificial Intelligence

Artificial Intelligence

Transcending fantasy, AI concepts expanding into real-world usage.

Artificial intelligence (AI) is usually associated with human-like computers such as Isaac Asimov’s positronic robots and the Star Wars droids. In truth, AI has moved way beyond the realm of fantasy and into the mainstream thanks to a range of new products, technologies and applications.

Virtual assistants such as Siri, Google Now and Cortana are AI applications that are becoming commonplace. Many retailers are using AI predictive analytics to offer personalized advertising, coupons and discounts. Spotify, Pandora and Netflix use similar systems to recommend music and movies. Countless other organizations use basic AI apps to automate data entry, analyze contracts, manage investment portfolios, filter job applicants and more.

AI is really an umbrella term for a number of technologies such as deep learning, machine learning, computer vision and natural language processing. All are aimed at embedding machines with the ability to analyze massive data sets, identify patterns and make autonomous decisions — eliminating the need for programmers to write code for every function.

While some technology futurists say that AI will eventually reshape the business world in ways rivaling the Industrial Revolution, its present-day uses are still evolving. Analysts say AI technologies have use cases and applications in almost every industry, and promise to significantly change existing business models while simultaneously creating new ones.

Tractica, a research firm focused on the AI market, has identified nearly 300 real-world AI use cases across 30 industries. The firm forecasts that revenue for AI applications will increase from $9.5 billion in 2018 to $118.6 billion by 2025, representing a significant upgrade over the firm’s previous projections.

Powering Automation, Analytics

It’s still very early in the AI game, and few organizations have fully developed plans for how to integrate AI into their operations. In a recent survey of 1,600 senior business decision-makers at large organizations across seven markets, Infosys found that big-data automation (65 percent) and predictive/prescriptive analytics (54 percent) are the primary AI applications in use today.

Those using AI technologies seem to experience immediate results. Infosys reports a clear link between an organization’s revenue growth and its AI utilization. Companies with mature AI strategies reported faster revenue growth over the past three years when compared to companies without such strategies

Organizations that have already deployed or have plans to deploy AI technologies expect to see a 39 percent average increase in revenue by 2020, alongside a 37 percent reduction in costs. On average, the companies surveyed have invested $6.7 million in AI in the past year, and have been actively using AI for an average of two years. Three-fourths of the Infosys respondents said AI is pivotal to their continued success, and 64 percent said future growth is dependent on large-scale AI adoption.

“Artificial intelligence adoption is on the rise and we are excited to see the investments in AI that businesses are gradually making to derive meaningful and creative change,” said Infosys President Sandeep Dadlani. “The achievements are remarkable and the opportunities AI is bringing forth are vast.”

While 71 percent say the rise of AI in the workplace is inevitable, 88 percent also note adoption-related challenges. For most organizations — particularly smaller businesses — finding and hiring data scientists, AI experts or people with deep expertise in data analytics is nearly impossible.

Starting Small

Getting started with AI doesn’t necessarily hinge on specialized staff, however. Smaller organizations can access a variety of online resources to get familiar with AI possibilities and explore ways to incorporate analytics and learning applications with heavy software coding. Stanford University and Columbia University offer AI-focused online courses, as does the online university Udacity. Tech incubators such as Techcode and Singularity University offer consulting services for organizations looking to incorporate AI tools.

Additionally, software developers are offering a growing array of apps to help smaller businesses incorporate AI tools into their operational processes and workflows. Quill, a natural language generation program from Narrative Science, weaves data into written documents to simplify report generation. SalesforceIQ combines data from email systems, smartphone calls and calendars to automate data entry for customer relationship management platforms.

Even the biggest players in the tech world understand the importance of making AI accessible to organizations of all sizes. IBM is working to bring the deep-learning and data analysis capabilities of its Watson AI platform to users through the cloud. Microsoft, meanwhile, is enabling users to run deep- learning training jobs, data rendering, real-time analytics and more accelerated tasks in its Azure cloud platform.

The cloud, in fact, represents a vital intersection for AI. Because deep learning involves analysis of large datasets, AI platforms need a cloud element for accessing cloud storage. The cloud allows organizations to utilize compute-intensive jobs without implementing an AI framework onsite.

“We're working hard to empower every organization with AI, so that they can make smarter products and solve some of the world's most pressing problems,” said Harry Shum, executive vice president of the Artificial Intelligence and Research Group at Microsoft. “AI is now within reach of any business.”


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