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Rethinking Enterprise Business Processes Using Artificial Intelligence

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Rethinking Enterprise Business Processes Using Artificial Intelligence

If you're part of an enterprise, then you need to rethink your business processes to account for both artificial intelligence and augmented intelligence.

· AI Zone
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In the 1990s, there was a popular book called Re-engineering the Corporation. Looking back now, re-engineering certainly has had a mixed success — but it definitely has had an impact over the last two decades. ERP deployments led by SAP and others were a direct result of the business process re-engineering phenomenon.

So, now with the rise of AI, could we think of a new form of re-engineering the corporation... using artificial intelligence? The successful robotic process automation companies have been focused on the UI layer. We could extend this far deeper into the enterprise. Leaving aside the discussion of the impact of AI on jobs, this could lead to augmented intelligence at the process level for employees (and hence an opportunity for people to transition their careers in the age of AI).

Here are some initial thoughts. I am exploring these ideas in more detail. This work is also part of an AI lab that we are launching in London and Berlin in partnership with UPM and Nvidia for both enterprises and cities.

How would you rethink enterprise business processes using augmented intelligence?

To put the basics into perspective, we are using a very "grassroots" definition of AI. AI is based on deep learning. Deep learning involves automatic feature detection using the data. You could model a range of data types (or a combination thereof) using AI:

  • Images and sounds through convolutional neural networks.

  • Transactions such as loan approval.

  • Sequences, including handwriting recognition via LSTMs and recurrent neural networks.

  • Text processing, such as natural language detection.

  • Behavior understanding via reinforcement learning.

To extend this idea to process engineering for enterprises and cities, we need to do the following:

  • Understand existing business processes.

  • Break the process down into its components.

  • Model the process using data and algorithms (both deep learning and machine learning).

  • Improve the efficiency of the process by complementing the human activity with AI.

But this just the first step. You would have to consider the wider impact of AI. This means focusing on the following:

  • New processes due to disruption at the industry level (for example, Uber changing the game).

  • Change of behavior due to new processes (for example, employees collaborating with robots as peers).

  • Improvements in current business processes for enterprises i.e. customer services, supply chain, finance, human resources, project management, corporate reporting, sales, logistics, and management.

  • The GPU-enabled enterprise (see Nvidia Grid) — but more broadly, how GPUs will democratize the delivery of modern apps, bring a more efficient hybridization of workflows, and unify compute and graphics.

  • The availability of bodies of labeled data.

  • New forms of communication such as text analytics, natural language processing, speech recognition, and chatbots.

What do you think about the potential impact of both artificial intelligence and augmented intelligence?

TrueSight is an AIOps platform, powered by machine learning and analytics, that elevates IT operations to address multi-cloud complexity and the speed of digital transformation.

Topics:
ai ,enterprise ,business processes ,neural networks

Published at DZone with permission of Ajit Jaokar, DZone MVB. See the original article here.

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