Will AI improve our work-life balance?

The promises made by Artificial Intelligence (AI) evangelists are many, manifold and multifarious.

We’re about to step into an era of computing where AI and all forms of Machine Learning (ML), neural network intelligence, and the lower chasms of so-called deep learning, will help us to automate the world around us and create more efficient work practices.

Few people would argue that any mission to help expedite our working processes is an admirable cause.

Grunt work killer

Fewer still would vilify any new innovation designed to help alleviate the ‘grunt work’ repeatable element of work (something that AI is inherently good at) and so free us up to work on more creative pursuits.

But will all of this automation actually make us happier?

Will workaholics still work too much, or will they start to realize that they now have an opportunity to address their work-life balance and start to manage their total existence more holistically?

AI purists tell us that part of the answer comes down to how well IT engineering departments provision for these new streams of intelligence. It’s all very well buying into a new AI initiative, but if the backend systems can’t support the new (smarter) front end, and service failures are rife, then the system will fail to deliver.

Bringing AI online, in the modern business arena, appears to start with core process planning, fundamental architectural configuration tasks, and data management first and foremost.

Then… and only then, can enterprise start focusing on the really smart stuff.

Endless AI-enhanced productivity

Nick Mayes, research lead and principal analyst at Pierre Audoin Consultants argues that businesses must focus on effective practices by getting their data and processes in order and making it easier for employees to access the information they need, when and where they need it.

“With these fundamentals and the right technology in place, the possibilities for AI-enhanced productivity are endless, from providing adaptive experiences based on context and location, to intelligent assistance and a highly-personalized service for each individual,” said Mayes.

There are wider arguments to be tabled here. Industry analysts, vendors and commentators in this space talk about the need to create the right kind of culture for AI advancements to flourish within.

Organizations across all verticals may actually have to look at re-engineering their business models (and in some cases, their actual go-to-market commercial strategies) in order to take advantage of new AI enablement.

Workplace productivity quotient

Once we accept the need to go through a thorough AI planning, preparation, and provisioning stage, then we can start to identify where individual workers’ jobs can be augmented by the use of digital virtual assistants.

These workers will be able to shape and tune their roles through the use of AI to create what the industry likes to call personalized and adaptive user experiences— this is the point where we can start to make AI work for us and hand over the tasks that we know machine brains ‘enjoy’ doing.

It’s still hard to gauge quite how far AI will really start to help tilt the work-life balance in our favor and start to make our lives better.

What we can say with some certainty is that if enterprise looks to engineer chatbots, virtual assistants and all forms of intelligent automation into our workplaces with a human-centric approach, then AI will make work better for everybody.

It is perhaps not so much a question of what AI can do. It may be more down to a question of what humans would prefer not to do… and even the most intelligent AI systems may not be appropriately engineered for those tasks yet.

Longer term, that problem becomes smaller, because AI is built to learn, obviously… so your future workplace could and should be a more pleasant environment to exist in.