"Near-term opportunities for cognitive systems are in industries such as banking, securities and investments, and manufacturing," said Jessica Goepfert, program director, Customer Insights and Analysis at IDC. "In these segments, we find a wealth of unstructured data, a desire to harness insights from this information, and an openness to innovative technologies. Furthermore, the value proposition of cognitive systems aligns well with industry executives' chief priorities. For instance, cognitive technologies are being used in the banking industry to detect and combat fraud – consistently a top industry pain point. Meanwhile, in manufacturing, executives cite improving product quality as a top initiative. In this case, cognitive systems recognize and know how to respond to dynamic fluctuations in product specs by adapting the production to stay within quality targets."
The industries that will invest the most in cognitive/AI systems in 2016 are banking and retail, followed by healthcare and discrete manufacturing. Combined, these four industries will generate more than half of all worldwide cognitive/AI revenues in 2016, with banking and retail each delivering nearly $1.5 billion. Healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3% and 61.4%, respectively. Education and process manufacturing will also experience significant growth over the forecast period.
Nearly half of all cognitive/AI revenue throughout the forecast will go to software, which includes both cognitive applications (i.e., text and rich media analytics, tagging, searching, machine learning, categorization, clustering, hypothesis generation, question answering, visualization, filtering, alerting, and navigation) and cognitive software platforms, which facilitate the development of intelligent, advisory, and cognitively enabled solutions. As both the largest and fastest-growing category, cognitive applications spending is forecast to reach $18.2 billion in 2020. Cognitive/AI-related services (business services and IT consulting) represent the second largest revenue category while hardware revenues (primarily from dedicated purchases of servers and storage) will grow nearly as fast as software with five-year CAGRs of more than 60%.
Hottest AI technologies:
1. Natural Language Generation: Producing text from computer data. Currently used in customer service, report generation, and summarizing business intelligence insights. Sample vendors: Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science, SAS, Yseop.
2. Speech Recognition: Transcribe and transform human speech into format useful for computer applications. Currently used in interactive voice response systems and mobile applications. Sample vendors: NICE, Nuance Communications, OpenText, Verint Systems.
3. Virtual Agents: “The current darling of the media,” says Forrester (like Amazon Alexa), from simple chatbots to advanced systems that can network with humans. Currently used in customer service and support and as a smart home manager. Sample vendors: Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft, Satisfi.
4. Machine Learning Platforms: Providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train, and deploy models into applications, processes, and other machines. Currently used in a wide range of enterprise applications, mostly `involving prediction or classification. Sample vendors: Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, Skytree.
5. AI-optimized Hardware: Graphics processing units (GPU) and appliances specifically designed and architected to efficiently run AI-oriented computational jobs. Currently primarily making a difference in deep learning applications. Sample vendors: Alluviate, Cray, Google, IBM, Intel, Nvidia.
6. Decision Management: Engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning.
7. Deep Learning Platforms: Currently primarily used in pattern recognition and classification applications supported by very large data sets. Sample vendors: Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, Sentient Technologies.
Deep Instinct is the first to apply deep learning to cybersecurity. They claim superior zero day attack production for endpoints and mobile devices.
Mumbai-based Fluid AI was founded in 2008, by two brothers Abhinav Aggarwal and Raghav Aggarwal, with a belief that the power of artificial intelligence can be used across industries, sectors and use cases. They have about a staff of 50 now. Fluid AI offers machine learning driven decision making for various business operations, and on the other it is creating virtual customer assistance for firms with a physical presence.
AI Driven Operational Decision Making
“The AI technology uses genetically evolving neural networks to create over 100,000 iterative models from the data sources given to us by the clients. It studies the data pattern which arises from the model evolves accordingly and improves feedbacks whenever the market conditions change.” says Abhinav.
The company offers a Plug and Play artificial intelligence system, which can be installed in any system. It connects to hundreds of data sources within and outside the server and gives the suggestions based on the previously collected data.
9. Robotic Process Automation: Using scripts and other methods to automate human action to support efficient business processes. Currently used where it’s too expensive or inefficient for humans to execute a task or a process. Sample vendors: Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, WorkFusion.
10. Text Analytics and NLP: