AI Integration – a better approach

Article Synopsis :

Robotics, artificial intelligence, and machine learning should not be seen as separate technologies any more. They must also be integrated into digital strategies that function alongside human workers. Retailers and consumer goods manufacturers must Move from evaluating individual elements and solutions to an approach that tackles the whole technology ecosystem.

AI must help people work smarter

AI needs a new development model

We are at a watershed moment in the adoption of these technologies. This point has been predicted – in science fiction as both the start of a new social contract and the beginning of the end for humanity as the machines replace people.

However, as our understanding of the subject has increased, so the way we develop the technology becomes more sophisticated.

The old model of selling technology into a company that immediately struggles to integrate it should be consigned to the dustbin of history.

A new starting point

What is needed is an integrated model that starts by linking digital strategy design with how that strategy will be used in the and by the workforce. This ‘integrative’ model will engage vendors, workers, and managers in collaboration on the design and bring technical and business knowledge to bear on the real-life business operations. Instead of wondering how this wonderful piece of kit can be used in the business, considerations of how technology can assist human inputs or fully replace it will be the jumping off point.

Where AI can add value

AI can successfully replace areas that have frequent, structured, and specific tasks. It works best where there are a greater number of events or data points in order to promote learning.

Within insurance, it is appropriate for AI to evaluate health claims in countries with standard codes, because those claims are both frequent and structured.

Where it does not work as well, is where decisions require human judgement, such as serious bodily injuries. AI might assist by providing data in order to make those decisions, adding value by augmenting the work.

Repetitive tasks in banking operations involving data entry and re-entry, particularly for compliance, reconciliation, and accounting purposes are another place AI will succeed. Software bots function like humans, but humans would not be able to handle an increase in data volumes. In this case, RPA will free up time for human workers to be deployed on more complex and analytical tasks.

Work smarter: collaborate

The author says not to throw technology at a problem, but look for elegant solutions to problems and ask how technology can help workers achieve the end goal faster and cheaper.

By shaping the technology to augment – rather than replace – human inputs, implementation can be far more effective.

Understanding this will improve the way technology is developed and implemented. A partnership is the way to achieve this. And that’s partnerships between groups that often see each other on opposite sides – technology vendors and business managers, between humans and machines, and between developers and the frontline workers.

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