The years after 2010 witnessed a massive revolution among all industry verticals; giant corporate houses, big and small enterprises were eager to join the digital bandwagon to transform their business operations and services. Some initiated their digital transformation journey with a big bang, deploying disruptive technologies at every level through a widespread transformational task. Others took baby steps and followed the approach of failing, learning, and finding their way. Adapting these digital technologies on such a large scale brought in the notion that businesses not leveraging digital technologies will be the last one and eventually become obsolete. Though it has led to a promising cycle where digital technologies leverage for more significant advantages, it has also created a fear of missing out (FOMO) among enterprises. This hype of technological advancements is nudging enterprises to jump into the digital transformation process without the much-required brainstorming.
What are Artificial Intelligence, Machine Learning, and Natural Language Processing?
Digital transformation is primarily about identifying major and minor gaps between processes while optimizing them to their full potential. With capabilities of integrating various organizational systems and automating routine and mundane tasks, digital transformation has touched new heights with Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML) based applications. Currently, we live in a reality where 90% of all the data ever produced in history was generated in the last two years. When the world is sitting on a data goldmine, we need tools and applications to provide this data with a usable meaning.
Here comes Machine Learning and Artificial Intelligence: the two key protagonists of digital transformation into the frame. These technologies are at the forefront of harnessing data to get critical insights and help enterprises in informed decision-making. AI, ML, and NLP are vital enablers of highly effective and increasingly innovative solutions that directly impact competitiveness, market growth, and customers’ expectations and experiences.
Critical Challenges AI is Addressing within Enterprises
With an increased shift toward improving customer experience, enterprises face some common challenges regardless of industry verticals. These challenges span across different levels and departments, but the cumulative effect, if unchecked, is profound. However, challenges, including data analytics, hyper-personalization, productivity issues, customer support, etc., can be easily mitigated with AI-powered solutions.
– Data Analytics & Insights
Enterprises can gain valuable data insights by analyzing different data sets generated from a specific business operation using artificial intelligence (AI) and machine learning (ML) powered tools. For instance, a business-specific machine learning model predicting the customer churn rate can also deduce factors responsible for the churn rate, thus helping decision-makers change business processes to decrease this rate.
– Employee Productivity Issues
Another critical area where AI tools make a significant transformation is employee productivity. The deployment of AI tools in managing redundant tasks like data entry, responding to general queries, and leading segregation in a marketing campaign leaves the human assets with more creative tasks. This automated support can increase employee satisfaction and productivity by manifold.
– Hyper-Personalization & Customer Support
The deployment of machine learning-based tools provides regular and 360-degree insights into customer behavior and buying patterns, thus opening doors for hyper-personalization. From AI-powered chatbots to 24X7 and faster help desks, enterprises utilize artificial intelligence to curate real-time data and provide a hyper-personalized customer experience to strengthen customer relationships while driving satisfaction, retention, and growth.
Is Automation Enough or Enterprises Should Invest in Human-AI Automation Collaboration?
Too often, enterprises are using just a fraction of the real potential of the deployed artificial intelligence and machine learning tools. Why? Because AI tools aren’t just for running the business cheaper and faster, its true worth lies in leveraging capabilities that can transform how work is done and the core business operations. To reimagine an entire organization, leaders need to think on a different tangent, which is way beyond the generic “command and response” model, and develop an exploratory, adaptable, and interactive experience. It is vital to understand that automating a process means getting a job done. However, the collaboration between automation, AI, and human engineers is a solution where the three would be in sync. The success of this collaboration, also known as Intelligent Automation, truly depends on the ability of an enterprise to ensure a better engagement between machines and humans.
In the end, everything boils down to competition among companies, and it can get pretty intense. For start-ups, the challenge is to survive among industry leaders. For industry giants, the challenge is the never-ending risk of becoming obsolete because of the ever-emerging disruptive technologies. Here, the key is nothing but innovation. Leveraging disruptive technologies like Artificial Intelligence and Machine Learning in various tools such as AI assistants can transform the entire business by improving efficiency, productivity, and customer satisfaction without increasing the headcount. We can keep customers and employees happy with one innovative AI-powered solution!