Enterprise AI is the biggest market for AI ML companies. If you are pursuing Artificial Intelligence Course in Gurgaon, it’s a great opportunity for you to get familiar with the latest trends and insights from the leading experts in Enterprise AI.
AI has many different roles and has many impacts on the various facets of life. In the last 5 years, we have seen AI dominating the IT and Digital Transformation journeys around the world. Almost every Fortune 500 company is either fully invested in or planning to invest in AI capabilities, and that has opened up the market for different types of AI development companies who are either piloting startup projects or assisting research groups with their AI innovations.
How Enterprise AI works and How is it Different from other types of AI Functions
As per industry experts, Enterprise AI is defined as the stream of advanced AI applications used specifically at an organizational level to drive various aspects of digital transformation. For a large part of the recent past, AI was largely a commoditized material for departments. For example, AI-based chatbots and virtual assistants were used in Marketing and Sales. Recently, we are also seeing the growth of AI tools in HR, Finance, Accounting, and IT streams. When the company adopts an AI application to transform each of its business process and verticals, cutting across strategic challenges related to back office automation, IT modernization, cybersecurity, and go-to market tactics.
IBM, a leader in Enterprise AI services, provides an AI platform to drive digital transformation for its customers. It is applied throughout their value chain. The result is highly effective in building business resilience, showcasing a much greater efficiency, agility, and flexibility within the organization. Externally, the organizations that adopt Enterprise AI are found to leave a much reduced environmental impact.
Recent Developments in Enterprise AI
The recent innovations in Enterprise AI highlight the role of emerging techniques like Open Source Programming, Virtualization, Hybrid Cloud Computing, DevSecOps, AutoML, AIOps, Edge/ Fog computing, and Quantum Computing applied across the organization. While these are still in their nascent stage, their role in Enterprise AI could leave an indelible mark on the developments happening around the world especially when we are so focused on creating a better remote workplace environment and build strategically agile IT infrastructures with 5G, IoT, and Cloud.
AI Cloud is a very powerful combination that allows customers to have full access to their IT resources across the organization. Providing a unified view to every data point and information, AI cloud helps customers to get answers to their varied queries at 10x speed, something which could only be dreamed of a few years ago if you were using a simple email, chat, and tele call system.
Today’s AI Cloud system unifies enterprise wide communication centers, connecting internal stakeholders, external partners, and customers for a fair and transparent interaction.
We are living in an era where merely having data is not enough. We are all trained to act and react like analysts, seeking undiluted information on every touchpoint within the enterprise. These are especially true for the top management who rely on Business Intelligence teams to report contextual information in real time so that decision making is quick and accurate. Embedded analytics, a very important product within the Enterprise AI technology stack, empower the users to bring in the combined synergy of business intelligence, data analytics, customer experience, and sales intelligence with predictive capabilities.
The result : The companies that use embedded Analytics in their enterprise AI technology stack generate 5x higher revenue from their AI investments, compared to those who are yet to invest in any AI tool.
We are working with tons and tons of data in our lifetime. From building a product to marketing and diversifying it in the market, data is the key resource. Yet, 90 percent of the data driven companies fail to protect and salvage their data. REASON – Poor governance and noncompliance to security practices.
Enterprise Content Management (ECM)
We recently published a post on ECM and the role of AI in it. AI, NLP, and Text Analytics are providing highly effective functionalities to modern ECM.
Enterprise AI helps close the gap between traditional data management systems and modern security infrastructures, bringing in the power of ECMs, Robotic Automation, autoML, and AIops to the core of every business transaction related to data science, management, and compliance.
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