HumBotAI - That's the way forward

Confused with the word #HumBotAI..? Well, that's going to be the future from here on. It's not another Chinese, Japanese OR Asian word which means any healing preaching or business/ war tactics :-). It is Humans, Bots & Artificial Intelligence (AI) working together. I am from the era when it used to be 'Employees are our greatest assets'. It still holds good but has slightly changed to "efficient employees are our greatest assets". And creating efficiency is not only the employee's responsibility but also equally with the corporates too. How does that happen..?

Humans in an organization do two types of work - Handwork (typing, clicking, etc.) and Mindwork (decision making, Analytics, etc.). Humans are the best doing the later until we have an alternative in technology. Till now all of the human's handwork can be replaced by a machine, to be specific a programmed bot. Let me reiterate, the main objective of the Bot automation is to empower employees to do more work and not replace them. Currently, process automation by bots can power new business process models, enabling organizations to gain greater value from data, systems, and human resources.

Then, how about Mindwork, can the human decision making be automated..?? Well, Yes to a certain extent. With the right technologies complementing each other in the most relevant ways, it’s possible to even raise operational efficiency, product quality, and service excellence to unprecedented levels. That's the power of Intelligent Automation.

What Is Intelligent Automation?

It’s a business automation strategy that integrates robotic process automation (RPA) with emerging artificial intelligence (AI) technologies like machine learning, natural language processing, and machine vision.

Working together in a way that leverages the unique strengths of each technology, this digital transformation toolset enables end-to-end and enterprise-wide process optimization.

How Does Artificial Intelligence Fit Into RPA?

In many ways, AI is the best companion for business automation efforts. RPA automates routine tasks, and AI can help improve user interfaces and analyze large amounts of data. The data analysis, machine learning, and predictive analytics capabilities of AI make it possible to automate many basic decisionmaking processes in an organization. Employing AI in a process also makes it possible to predict what needs to be done and be proactive in the process by analyzing patterns in historical data and anticipating any roadblocks or constraints.

What are User Benefits of AI?

There are many companies and most prominent large companies like Google, Microsoft, and Amazon are leading the industry in developing complex AI algorithms and APIs that can quickly and easily be integrated into RPA. Using these tools to add AI to RPA helps reduce the amount of time spent on certain tasks, improving customer experience, and reducing costs (without building a pool of data scientists and data modeling toolsets in-house). This cost-effective approach opens up many use cases that can be considered in organizational implementation, at least two broad categories. These AI benefit categories That can be of benefit to users in: natural language interfaces and data-driven insights derived from the larger context, in which the business exists.

1. Voice Interface

AI-driven natural language interfaces make interacting with an application easier and speed up the process. The AI interface can automate many of the steps just by understanding the words spoken and the business context of the request. In addition, AI and machine learning make it possible for an application to learn from each interaction and streamline the process for the next time. One advantage of AI is its ability to gauge intent from conversational dialogue (also in terms of sentiment analysis) to streamline and automate common tasks. By analyzing key phrases, AI can understand the intent and fill in the appropriate information.

1. Data-Driven insight

AI’s machine learning component can provide incredible gains in productivity. With each interaction, the system acquires more data about how decisions are made and apply statistical analysis to develop rules around decision-making. Efficiencies are achieved because machine learning looks at historical data and uses predictive analytics to spot trends and make business decisions based on this data.

Let's see a couple of cases

• Usecase 1 - Intelligent RPA can be used to observe, and learn, what people are actually doing, and then automate those patterns so people don’t have to do error-prone redundant work.
• Usecase 2 - Machine learning can be applied during process execution to, for example, trigger a new process or reroute running processes according to predictions.
• Usecase 3 - NLP can take unstructured data, both spoken and written, to understand the intent and automate business processes by grabbing actionable data to reduce the time and resources required to successfully complete business processes.

Looking forward, AI will be instrumental in improving the user experience within the business workflow, by applying other AI techniques on user interactions and browser uses, and by analyzing page flow.

How Business Benefits of Intelligent Automation?

• Compete on customer experience: Reduce response times, enhance service levels, and elevate product quality. With the support of RPA and AI, humans can focus on the more complex customer service cases, to enhance the overall customer experience.
• Dive deeper into your data: Can easily connect and integrate data systems into the process management tools. If data is unstructured, AI can transform this into a bot-friendly format, while also unlocking insights that augment human decision-making capabilities. Also, helpful in process mining your data to get valuable insights.
• Support compliance and risk management: Meet regulatory obligations more efficiently (all the time), access process data in real-time, and enable granular reporting to meet your audit defense goals.
• Re-think roles: Empower human workers to shift their focus towards higher-value tasks that require strategic thought, creativity, and/or professional judgment.

Conclusion

Ultimately, we need to make sure that we understand the unique value that each technology brings to the table, so we can re-engineer processes & utilize technology accordingly. It’s also important to hold your intelligent automation strategy together with a foundation that is agile, scalable, adaptable, and user-friendly. Humans-Bots-AI is going to give better customer experience and also make employees feel satisfied with the same job they are performing every day, for a longer time. It's always advised to start small with automation and scale as the needs grow by easily integrating RPA and then leveraging AI services from a range of third-party providers as and when we need them. When intelligent automation is well-planned and executed, organizations can unlock new revenue streams, enhance profitability, transform the customer experience, and stay ahead of the rest.