AI penetration in the enterprise world is moving to new heights. In fact, studies show that businesses worldwide are allocating an average of 10% of their IT budgets to AI initiatives. From Generative AI to intelligent analytics, the scope of the use of AI in critical operational areas is growing daily. But the real deal will be when AI can help businesses make the most informed decisions on strategies.
For long, this was deemed a very complex journey. The major reason for the complexity was the large pool of unstructured data that lingered around the digital landscape of businesses. Studies estimate that by 2025, nearly 80% of the 175 Zeta bytes of data created globally will be unstructured in nature. But today, the rise of cognitive automation is fueling a new wave of AI-led decision-making approaches across businesses in different sectors.
What is Cognitive Automation?
In simple terms, cognitive automation refers to the practice of applying AI to traditional business process automation initiatives. The combination allows enterprises to enhance outcomes in key business activities by making use of AI components like machine learning, visual analytics, natural language processing, etc. By using a combination of these approaches, enterprises can get their AI systems to mimic human decision frameworks or cognitive thinking capabilities and power business operations autonomously.
A simple example could be an AI mail bot reading and understanding the context of an email and taking appropriate action to initiate a process to meet the demands raised by the sender through the email.
Solving the Unstructured Data Puzzle
The real power of cognitive automation lies in the ability of enterprises to make meaningful inferences and decipher valuable insights from heaps of unstructured data. Not all data in the world comes in a ready-to-use sorted format stored in rows and columns of a database table. The data that businesses get today comprises everything from simple transactional information to social media sentiments, emails, chats, videos, images, and dozens of human interactions across digital and physical channels.
In the past, this unstructured data had to be first refined and converted into a meaningful format before being processed to extract insights. These insights could then be used by decision-makers to execute business actions accordingly. But fast forward to today, cognitive automation can eliminate the lengthy process of preparing structured data from high volumes of unstructured information. Instead, it can directly extract key insights from any kind of data irrespective of whether it is structured or unstructured, and use the insights to execute even critical business responses or outcomes.
The Real Benefits of Cognitive Automation in the Enterprise Value Chain
Now we know that AI helps in enhancing automation capabilities by bringing a cognitive angle to unlock insights from even unstructured data. Let us then explore the potential areas where cognitive automation can help bring better value for enterprises with informed decision-making:
- Faster Responses
With cognitive automation, enterprises can build unbelievably fast response systems for customer interactions. For example, a social media response system that uses cognitive automation to understand the true intent of the brand mentions anywhere on a social platform. The outcome here would be the system autonomously replying to the sentiment to pacify any negativity and build trust through intelligent conversations.
- Autonomous Operations
Decision-making improves when an organization can have intelligent workflows and automated operations at deeper levels. With cognitive automation, it becomes easier for autonomous decision-making even at granular levels of the business without human intervention. For example, deciphering a customer request from an email or chat can be handled by a Generative AI-powered bot that is also connected to an automated workflow that pulls out the information needed on demand from across the business's digital landscape. The entire process works autonomously and independent of any human worker. This can be scaled to cover multiple business activities over time.
- Increased accuracy
As AI systems work to understand the true meaning of transactional data coming in through a wide variety of channels in structured or unstructured format, the subsequent inferences made, or decisions taken will be more accurate than traditional automated systems. The reason is that the outcomes are highly influenced by the AI system working behind the scenes. Using cognitive intelligence, it can learn in-depth about the potential outcomes for each scenario and then make a choice based on the data captured.
Getting better ROI with Cognitive Automation
Cognitive automation is undoubtedly a fantastic technology approach that brings AI closer to an enterprise’s digital core. However, leveraging cognitive automation for revamping operations is not an easy task. From selecting the right tools to ensuring sufficient training data for the AI system, the challenges are plenty. This is where an experienced technology partner can be a major game changer. Get in touch with your partner to explore more.
