By Seng Sun of SunView Software
The proliferation of AI technology in today’s workplace has made a global impact on the way business processes are managed at both small and enterprise levels. Businesses are transforming traditionally reactive services into proactive automations using technologies engineered with machine learning and big data processing power. The result — faster and more calculated decisions and better business outcomes. And with adoption rates of AI-powered enterprise technologies rising at an accelerated rate, we’re still pioneering what Google’s CEO Sundar Pichai has described as an “AI-First World” shift in modern computing.READ MORE: Amazon Web Services Reports Major Outage; Netflix, Venmo, Instacart Among Many Affected Sites
AI Makes An Impact
Artificial Intelligence has made a huge splash in the enterprise application space. AI-powered technologies like deep learning, reporting and communication automations, natural language processing, recommendation engines and more have slowly crept into most SaaS business applications, and they’re only becoming more prolific — especially when it comes to data. According to Gartner, “61 percent of enterprises with an innovation strategy are applying AI to their data to find previously missed opportunities such as process improvements or new revenue streams.”
Of all of the permutations of AI in the enterprise, one of the most widely accepted has been predictive analytics, as it helps organizations obtain real value from their data. Predictive analytics goes hand-in-hand with Big Data, a noteworthy movement in its own right, by actively analyzing data and predicting trends in real-time in order to provide insight into future behavior. This automated analysis technology provides nearly unlimited application potential for digital organizations that want to take full advantage of their company and consumer data. It has also proved to be popular among virtually all enterprise market sectors. In fact, it may be the only way for companies, especially those smaller firms with limited resources, to manage the enormous flow of information. Gartner predicts that, “by 2020, 40 percent of the new investment made by enterprises will be in predictive analytics.”
The Applications Of AI In The Real-World
AI has certainly been the talk of the collective business tech community, as companies develop and implement intelligent features to meet the demands of their users. CRM automation juggernaut Salesforce recently launched Einstein, a mechanism that delivers AI applications across their entire platform. Einstein uses predictive lead scoring to help sales teams identify more likely candidates and new opportunities. It also contextualizes key information like when a competitor’s interest makes headlines, equipping teams with critical insights while they work their territories. The technology works in a similar vein to Inside Sales NeuralView, which intelligently crawls data to predict the most likely purchasing funnel prospects. Competition to have the smartest sales automation tool on the market is growing by the day.
However, while AI and smart technologies have been successfully assisting sales teams hungry for closing deals, they have also begun to integrate with the IT and Service Management organizations that serve the more operational parts of the business. Advances in smart IT software developed with predictive analytics, machine learning and more now provide a strong foundation for better customer engagement and a faster, more productive service desk. AI-powered technology like machine learning is also helping IT companies to work more efficiently. In fact, Gartner states that by 2019, “IT service desks utilizing machine learning enhanced technologies will free up to 30 percent of support capacity.”READ MORE: 'Prolific' San Francisco Retail Theft Suspect Back In Jail After New Arrest
AI has proven useful for IT in other ways as well. For example, today’s IT service desk platforms are being developing with AI functionality that augment user interactions and provide real-time predictive insights and recommendations based on an organization’s own historical data. These technologies can help IT staff quickly fill out and resolve incident tickets, and provide end users more engaging self-service options. For example, Chatbots can understand simple questions and respond in helpful ways like searching the knowledge base for solutions or helping the user to submit requests faster and more accurately.
The future of smart applications in the business world is bright, and we’re just now seeing the tip of the iceberg. Organizations from small to medium businesses through the largest enterprises are only at the start of their journey with AI, and are fast learning the true potential of the technology.
Seng Sun founded SunView Software in 2003 to pursue his entrepreneurial dream and create a change management solution for those in IT. He currently serves as CEO and recently helped SunView introduce one of the first artificial intelligence and machine learning solutions for ITSM.
The views, opinions and positions expressed within this guest post are those of the authors alone and do not represent those of CBS Small Business Pulse or the CBS Corporation. The accuracy, completeness and validity of any statements made within this article are verified solely by the authors.
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