If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
AI is finding its way to more places in organizations, including human resources. Human capital management providers are building AI into their solutions, but depending on the details, it may be wiser to build your own application than buy something off-the-shelf. Earlier this year, Gartner issued a research note exploring AI use cases in human capital management (HCM). Its author, VP Analyst Helen Poitevin, concluded that many of these applications were still in the "demo candy" stage, mainly to demonstrate product roadmaps. In other words, AI-related expectations are outpacing reality.
What if a few clicks on the keyboard could transform an ordinary, mild-mannered business software user into a future-seeing data warrior? This scenario may sound like a far-fetched, super-hero story. But, this remarkable capability is within grasp. A new breed of artificial intelligence (AI) solutions are creating the role of citizen data scientist, a professional without code development skills, but the ability to apply automated insights to business questions. Automation is a big driver of this trend.
One of the biggest problems health plans face is dirty data, says Jordan Bazinsky, executive vice president and administrative officer at Atlanta-based Cotiviti. The healthcare solutions and analytics company reports having "several hundred" health insurance companies among its clientele, including 24 of the top 25 plans, he says. "Dirty data is one of the key problems that blocks health plans from finding insights from data," Bazinsky says. "You might be able to push data real-time, but if you can't trust the underlying kernel of data--all the other things can't be trusted." According to Bazinsky, Cotiviti uses data analytics to help payers achieve financial health through payment accuracy that is appropriate to the care delivered.
Webhelp recently commissioned revealing new research from polling experts YouGov, designed to uncover what 2,000 British adults really think about Artificial Intelligence (AI). The report explores the public perception of how AI technology will change the way brands provide customer service. Webhelp's Global Analytics Director, Chris Bryson, takes a closer look at the findings: Rules in CX are being rewritten. It's getting harder to predict the future but we can still try. In the evolving digital marketplace, as customers become more exposed to AI systems, it is critical that businesses consider new strategies for the future of shopping without human-to human contact.
Two City firms have backed a lawtech startup's initiative to create a new standard language of contracting by analysing millions of existing contracts with machine learning software. 'Lexible' is a continually updated dictionary of contract terms which is claimed to have the potential to save huge amounts of lawyers' time by standardising the interpretation and review of contracts. The announcement, by UK startup ThoughtRiver, is signficant because it marks one of the first attempts to exploit the knowledge accumulated by commercial artificial intelligence systems being installed by City firms and in-house legal departments to take on the grunt-work of contract review. ThoughtRiver says its standard language of reference terms is based on an analysis of 4 million documents. This analysis revealed wide variations in phrasing: for example in 1.4 million contracts, a simple governing-law clause was expressed in 330,000 different ways.
For the modern enterprise, services done well often drive growth. For example, quality IT infrastructure services and/or outsourced marketing can accelerate a company's competitive advantage in multiple ways. Although it's sometimes hard to measure the specific outcomes that services yield, they can have a major impact on a company's results, such as with more successful marketing campaigns, digital transformations, legal wins or other organizational efforts. That's why, in recent years, many Fortune 100 companies have significantly increased spend on service providers to meet competitive, productivity and business velocity demands. Companies can't hire and cultivate enough internal expertise as the work gets more sophisticated and specialized and the opportunities more global.
Exxact Corporation, a leading provider of high performance computing solutions (HPC) for GPU-accelerated deep learning research, announced that its NVIDIA T4-powered Deep Learning Inference Servers are now shipping worldwide. Exxact Deep Learning Inference Servers bring revolutionary multi-precision inference performance to efficiently accelerate the diverse applications of modern AI. Powered by NVIDIA T4 GPUs, Exxact Deep Learning Inference Servers are optimized for use in image and video search, video analytics, object classification and detection, and a host of other scenarios. The NVIDIA T4 is the most versatile GPU to date -- bringing dramatic performance and efficiency gains to both deep learning training and inference. Built on NVIDIA's Turing architecture, the T4 also includes Tensor Cores for acceleration of deep learning inference workflows.
Change Healthcare AI can help providers identify problem claims and prevent denials before they happen, avoiding costly rework, delays, and improving revenue flow. Today Change Healthcare announced that it has applied its Claims Lifecycle Artificial Intelligence (AI) technology to its claims management suite with the introduction of Assurance Reimbursement Management Denial Propensity Scoring and Revenue Performance Advisor Denial Prevention. With performance enhanced by Claims Lifecycle AI, providers of any size can now proactively identify problem claims that could result in denials, and remediate potential issues before the claims are filed. The AI infused in these applications can now help customers predict denials, optimize claims submissions, and provide actionable recommendations that enable providers to better mitigate denials before a claim is submitted. Change Healthcare's analysis of 2018 data spanning more than 500 million service lines showed that Change Healthcare Claims Lifecycle AI could identify and flag up to 35% of denials prior to submission.
Employees and contractors at the Centers of Medicare and Medicaid Services spend countless hours every year reviewing thousands of medical records to ensure the accuracy of Medicare Advantage payments. An automated intake tool is working to change that. Using emerging technologies such as robotic process automation, optical character recognition, machine learning and artificial intelligence, KPMG's Intake Process Automation Tool ingests records as they are submitted and identifies potential problems according to set parameters, submission rules and coding guidance. Specifically, RPA orchestrates the steps of the intake process, OCR digitizes the scanned document and then AI and machine learning are applied to understand the document and extract the information necessary to validate the information. Intake PA stands to save CMS time and money, said Payam Mousavi, KPMG's lead director for intelligent automation for governments and the technical lead for the CMS project.
Voice-powered virtual assistants have huge potential for improving and expanding clinical trials, and tech companies are moving quickly to develop artificial intelligence-based software that can support and also protect the most private conversations between patients and clinicians. Katherine Vandebelt has already started scribbling down ideas about how voice assistants could work in a clinical trial environment. As Oracle's global head of clinical innovation, and former clinical innovation leader at Eli Lilly and Company, Vandebelt believes that the clinical trial experience can change with the introduction of virtual assistants into the drug research ecosystem. In April, Amazon's Alexa app became compliant with the US government's Health Insurance Portability and Accountability Act (HIPAA), and similar virtual assistants are likely to follow. Here are five changes she sees coming.