AI in the Enterprise

AI is a top-line impact accelerating factor, pioneering disruption and opening up endless market opportunities for enterprises, ranging from corporate communication and network security management to key workflow automation. This article sums up the main applications of artificial intelligence in business, significant challenges and the future of AI investments.

As more and more organizations accelerate their digital transformation rates, new platform business models emerge. Using these models, enterprises can make greater use of data and fulfill strategic business goals through enhanced customer service, optimized operations and better employee experiences.

Digital transformations in organizations co-occur: from the outside in and the inside out. Outside-in reinvention comprises new ways to engage and facilitate customer interactions while being accountable for the massive data volumes now in the organization's hold. The inside-out transformation manifests through blockchain, AI application capability, Internet of Things (IoT), automation, cloud, quantum computing and 5G.

The openness of business platforms across the ecosystem is currently in progress, culminating in a Virtual Enterprise. The return on investment of a Virtual Enterprise compound from the resultant ecosystems, digital workflows, and networked organizations by expanding intelligent workflows and virtualized operations over more extensive systems. A "golden thread" of value that animates and connects ecosystem players drives the Virtual Enterprise. The virtual enterprises' key characteristic is an innovation driven by data—the openness facilitates access to the creation of services and products with the help of AI and other innovative technologies.

AI Adoption Challenges

● Strategic perception: Organizational intricacy grows with the adoption of Virtual Enterprise. Many enterprises do not have a realistic plan and strategy, which poses a severe challenge.
● Implementation: A primary challenge for most enterprises with their digital transformation progress is delivering digital transformation at scale. How quickly and to what extent can the existing business model be reinvented?
● Lack of knowledge of different artificial intelligence is also a major limiting factor. Clients need to know how to navigate incompetency and deploy new technologies, data and the existing ecosystems to drive solutions.

Once a company eliminates barriers to deployment and adoption and uses automation solutions and AI to overcome these obstacles, it can derive an economic value for its stakeholders.

AI in the Enterprise

AI investment areas for businesses range from knowledge and workforce development to purchasing AI solutions and integrating them into various business functions, developing agile learning systems that will efficiently and effectively build applications.

In the coming months, AI investments will increasingly level the fundamental defining capacities of AI for business – IT and process automation, establishing trust in the outcomes of AI, and mastering the business language. Data-driven and predictive business models, risk awareness, security and intelligent automation are becoming the industry norm for most enterprises. By incorporating AI into core processes, such as customer service, employee experiences, business functions, IT and finance, business leaders create companies with agility and speed.

As customers continuously discover new, disruptive ways for transformation using AI and hybrid cloud, these investments continue to multiply.

Learn more about AI and figure out how to deliver economic value for your business and clientele.

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