How Machine-Human Collaboration Is Boosting Innovation at Work

The machine vs. human mindset is obsolete. Now, future success involves coming to terms with the concept of “machine plus human” and how this unlikely partnership can boost innovation in the workplace.

By Michael Brenner

By Michael Brenner August 18, 2020

The era of Artificial Intelligence (AI) has well and truly dawned. The way we live, work, and conduct business is transforming. Companies looking to future-proof their processes are increasingly using AI technologies to expand their business. It’s evident in manufacturing, where robots share our environment to supply chains that react in real time, 

This is a time of change – and change doesn’t wait. Those that can understand – better yet, embrace – the concept of machine-human collaboration are set to succeed in the coming years. Those that ignore it, on the other hand, will undoubtedly be left behind.

Estimates suggest that if businesses invest in AI and machine-human collaboration at the same rate as top-performing companies, they can expect a revenue boost of 38 percent by 2022 and raise employment levels by 10 percent. What’s more, 54 percent of organization leaders believe that machine-human collaboration is critical to achieving their strategic priorities.

The machine vs. human mindset is obsolete. Now, future success involves coming to terms with the concept of machine plus human and how this unlikely partnership can boost innovation in the workplace.

Business in the Age of AI

The emergence and adoption of AI technologies fosters new opportunities and creates new roles for humans on all levels of the value chain in IT and beyond. These new opportunities rely on AI’s capacity to transform business processes in several distinct ways:

Speed. Time is a critical factor in the IT space, as well as many other industries. For example, with AI at the helm, financial businesses can detect credit card fraud on the spot, saving valuable time and energy. HSBC Holdings is already using an AI-based solution to stop laundering, fraud, and terrorist funding.

Flexibility. Rigid processes are a thing of the past. AI enables manufacturing and other procedures to follow real-time customer choices.

Scale. Corporations working on larger scales can use AI to accelerate operations. For example, Unilever has adopted an AI-based hiring system that doubled job applicants to 30,000 and decreased hiring time from four months to four weeks.

Decision-making. Making decisions based on data is best practice in business. Machine learning and AI give workers access to vast amounts of tailored information to solve problems quicker and more effectively.

Personalization. AI makes on-demand customized brand experiences accessible at a significant scale. Music streaming service Pandora uses AI algorithms to generate personalized playlists based on user preferences.

How Machine-Human Collaboration Fosters Innovation

With enhanced speed, flexibility, scaling abilities, decision-making tools, and personalization processes in tow, businesses can focus on re-skilling their talent and redefining job descriptions to encourage creativity and innovation. This overhaul will be paramount for those that wish to remain relevant.

Here are a few ways machine-human collaboration has and will continue to foster innovation.

Rehumanizing time – Monotonous, repetitive tasks may be real-time killers, but they are also perfect candidates for AI. By enlisting the help of a machine, employees can forgo these duties in favor of human activities. For example, workers will have more time to focus on enhancing interpersonal interactions, improving their higher-level skills, following an idea to its completion, and innovating.

Machine-based empowerment – A whole variety of machines are available to help people in your business be more productive and ultimately become better at their jobs. With the power of AI agents by their side, employees can extend their capabilities and reimagine tired or outdated business processes.

Reciprocal training – Typically, technological education goes in one direction: People learn how to use machines. But, with AI, machines are learning from humans, and humans are learning again from devices. In the future, humans may perform tasks alongside AI; AI can provide on-the-job-training that will assist humans in understanding and utilizing AI-enhanced processes.

Reimagined business processes – The holistic reimagination of business processes will only be possible when humans create working mental models of how machines work and learn. And, this represents a significant opportunity for innovation. Without a creative spirit and a drive to improve customer experience, the potential of AI simply will not be reached.

Ethics in the workplace – A machine may be uncertain about something in particular or lack the required ethical context to make a decision. In these instances, humans will have to step in and provide input. Ethical dilemmas will come to the fore, and humans must be prepared to develop AI-based systems that account for these kinds of moral issues.

Constant rethinking – As AI becomes more accessible and more intelligent, humans will be tasked with the relentless rethinking of business processes. Innovation will be continually sparked by questions like:

  • How can new AI technologies improve the workplace?

  • How can new AI technologies streamline organizational processes?

  • Is there a better business model to follow in light of advances in AI?

Machine-Human Collaboration Is a Two-Way Street

Before we scrap existing business processes, models, and job descriptions and subscribe to the latest and greatest in AI hype, it’s vital to ask the following:

  • What do humans do best?

  • What do machines do best?

Machine-human collaboration is a two-way street. Many humans that work across various industries can off-load a significant portion of their current duties onto AI agents that will, most likely, perform tasks faster and with greater accuracy.

In many cases, machine-human collaboration asks us to shoulder more important responsibilities: interpersonal interaction, creativity, and innovation.

In short, AI frees up human capital, enabling humans to work like humans and not like robots.

Michael Brenner is a keynote speaker, author and CEO of Marketing Insider Group. Michael has written hundreds of articles on sites such as Forbes, Entrepreneur Magazine, and The Guardian and he speaks at dozens of leadership conferences each year covering topics such as marketing, leadership, technology and business strategy. Follow him @BrennerMichael.

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