Collaboration sits at the heart of any successful organisation. Effective collaboration has -- and always will -- come down to a company culture that nurtures and rewards engagement. The difference is that, increasingly, businesses are turning to technology to help make it happen.
We’re witnessing the emergence -- and rising popularity -- of conversational workplace platforms such as Slack, Google Hangouts, IBM Watson Workspace and Workplace by Facebook. These platforms operate as communication hubs, linking business units, teams and data sources. They can also integrate with third-party apps, and, according to research from McKinsey, improve a company’s productivity up to 30 per cent.
Such tools bring together teams -- remote or not -- through an ease of engagement that streamlines workflow. While collaboration platforms intend to facilitate a more productive work environment, the amount of information they provide can also be constant and overwhelming. Where artificial intelligence (AI) steps in intelligently with Slack, for example, is to help filter and prioritise messages using an algorithm called “collaborative filtering,” saving time and resources. That’s where the application of artificial intelligence – including machine learning and natural language processing -- can help.
By drawing on data and content to drive more insightful collaborative conversations, AI will help make decision-making easier and eliminate administrative tasks with the help of bots, or AI assistants like Hendrix.ai, the one developed by my company, Testfire Labs.
Much in the same way that home and mobile assistants learn about our personal routines and preferences, machine learning has the potential to recognise business opportunities, patterns and insights to drive collaboration among an organisation’s internal and external stakeholders. There soon will be no need, for example, to ask a colleague to send you an email with notes from a missed meeting: there’s a bot to do that for you.
While the rise of AI has ignited fear in some industries that jobs will be made redundant, AI is really about giving employees the space to be more effective in their roles. AI and machine-learning software will have its best success when it works alongside human skills to complement and augment capabilities, not replace them. This will spark a whole new area of collaboration in which the speed, scalability and quantitative capabilities of AI work are in harmony with the strengths that set humans apart: leadership, teamwork, creativity and emotional intelligence. Machines are not taking away human skills; they’re amplifying and assisting our skills, while giving us room for creativity.
Here are some supporting data:
In a recent survey of 1075 companies across 12 industries, researchers H. James Wilson and Paul R. Daugherty (authors of the book Human + Machine: Reimagining Work in the Age of AI, Harvard Business Review Press, 2018) found that the better companies were able to redesign business processes, embrace employee involvement, have an active AI strategy, responsibly collect data, and incorporate AI to complement employee skills, the better their AI initiatives performed in terms of speed, cost savings, revenues, or other operational measures.
PwC, the professional services company, has estimated that AI could be worth $15.8 trillion in increased global GDP by 2030. But adoption is still low. The publication MIT Sloan Management Review reported in 2017 on a study that surveyed 3,000 executives, analysts and managers from across industries. The study’s authors found that almost 85 per cent of executives view AI as a strategic opportunity, and 63 per cent expect AI to change their industry significantly in the next five years. Yet, less than 39 per cent of enterprises have an AI strategy. Only 15 per cent of enterprises are using AI, and only 5 per cent have extensive deployment throughout their business.
So, where’s the disconnect?
Put simply, as the usage and intelligence of AI assistants grows, so do people’s anxieties. And for many corporations, it comes down to a question of whether the benefits are worth risks such as:
Corporations are built on immense amounts of data – the vast majority of which is highly confidential and must remain private. And while artificial intelligence and machine learning models are becoming more ubiquitous, the general understanding of how they work to access, analyse, and utilise data remains an area of great uncertainty.
The proliferation of cameras, sensors in our smart phones and around our offices, and always-on voice assistants, are just a few examples of technologies that are contributing to society's radical shift in surveillance, carrying with them huge implications for our working lives. As more and more always-on systems for surveillance and monitoring are deployed within our businesses, they’re changing not only the way we work, but also heightening our feelings of paranoia and skepticism.
Google’s Duplex sparked an unexpected ethical debate around the use of voice assistants. We know people are getting more comfortable with AI, but we're still in the phase of wanting to experience something similar to what we're used to: something human. For that reason, companies will continue to make their voice assistants as human as possible, since they want people to have natural interactions with them. However, as AI assistants and the ethical considerations surrounding them continue to evolve, considerable effort will need to be applied to strike a balance between those who will want AI interactions to be identified as such, and those who will want their interactions to be as human and "normal" as possible.
As we accelerate the ways in which we apply artificial intelligence to analyse all of this data, we need to pause and consider how it will be interpreted, and how it will affect workplace behaviours, personal privacy, and trust.
This is not the rise of the robot
By removing repetitive, mundane tasks, AI will free employees to focus on tasks that require creative thinking, emotional intelligence, intuition or problem solving -- all important aspects of a successfully collaborative environment.
In this sense, AI is really about using decision-support systems to create work efficiencies, giving us the information and insights we need to quickly make decisions, so we have more time -- and headspace -- for productive, meaningful tasks.
Dave Damer, founder & CEO, Testfire Labs
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