Top 10 AI Technologies

The marketplace for Artificial Intelligence technologies is flourishing. Beyond the hype and therefore the heightened media attention, the various startups and therefore the internet giants racing to accumulate them, there's a big increase in investment and adoption by enterprises. A Narrative Science survey found last year that 38% of enterprises are already using AI, growing to 62% by 2018. Forrester Research predicted a greater than 300% increase in investment in AI in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to quite $47 billion in 2020.

Coined in 1955 to explain a replacement computing sub-discipline, “Artificial Intelligence” today includes a spread of technologies and tools, some time-tested, others relatively new. to assist add up of what’s hot and what’s not, Forrester just published a TechRadar report on AI (for application development professionals), an in depth analysis of 13 technologies enterprises should consider adopting to support human decision-making.Based on Forrester’s analysis, here’s the list of the ten hottest AI technologies:

1. Natural Language Generation: Producing text from computer data. Currently utilized 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 utilized 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 (I believe they ask my evolving relationships with Alexa), from simple chatbots to advanced systems which will network with humans. Currently utilized in customer service and support and as a sensible 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. A mature technology, it's utilized in a good sort of enterprise applications, assisting in or performing automated decision-making. Sample vendors: Advanced Systems Concepts, Informatica, Maana, Pegasystems, UiPath.
7. Deep Learning Platforms: A special sort of machine learning consisting of artificial neural networks with multiple abstraction layers. Currently primarily utilized 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.
8. Biometrics: Enable more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and visual communication . Currently used primarily in marketing research . Sample vendors: 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo.
9. Robotic Process Automation: Using scripts and other methods to automate act 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: tongue processing (NLP) uses and supports text analytics by facilitating the understanding of syntax and meaning, sentiment, and intent through statistical and machine learning methods. Currently utilized in fraud detection and security, a good range of automated assistants, and applications for mining unstructured data. Sample vendors: Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, Synapsify.

There are certainly many business benefits gained from AI technologies today, but consistent with a survey Forrester conducted last year, there also are obstacles to AI adoption as expressed by companies with no plans of investing in AI:


Once enterprises overcome these obstacles, Forrester concludes, they stand to realize from AI driving accelerated transformation in customer-facing applications and developing an interconnected web of enterprise intelligence.