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Future collaboration tools will use AI to gather relevant resources across the organization and provide much-needed context.

Artificial intelligence (AI) is usually associated with human-like computers such as Isaac Asimov’s positronic robots and the Star Warsdroids. In truth, AI has moved way beyond the realm of fantasy and into the mainstream thanks to a range of new products, technologies and applications.

Virtual assistants such as Siri and Cortana are AI applications that have become commonplace. Many retailers are using AI predictive analytics to offer personalized advertising, coupons and discounts. Spotify, Pandora and Netflix use similar systems to recommend music and movies. Countless other organizations use basic AI apps to automate data entry, analyze contracts, manage investment portfolios, filter job applicants and more.

AI is an umbrella term for a number of technologies, such as deep learning, machine learning, computer vision and natural language processing. All are aimed at embedding machines with the ability to analyze massive data sets, identify patterns and make autonomous decisions — eliminating the need for programmers to write code for every function.

Analysts say AI technologies have applications in almost every industry, and promise to significantly change existing business models while simultaneously creating new ones. Although present-day use cases are still evolving, some technology futurists say that AI will eventually reshape the business world in ways rivaling the Industrial Revolution.

Tractica, a research firm focused on the AI market, has identified nearly 300 real-world AI use cases across 30 industries. The firm forecasts that revenue for AI applications will increase from $9.5 billion in 2018 to $118.6 billion by 2025, representing a significant upgrade over the firm’s previous projections.

The Cost of Ineffective Collaboration

While AI applications tend to focus on specific industries, the technology has the potential to change the way knowledge workers interact by enhancing collaboration. AI tools could serve as the “eyes and ears” of the organization as a whole to ensure that functional teams have all the information and resources they need to perform optimally.

Today’s collaboration tools focus on facilitating specific functions, such as video conferences and file sharing. This functional approach to collaboration can actually cause bottlenecks that hinder productivity and derail projects.

According to the Workplace Productivity and Communications Technology Report from Webtorials, almost 15 percent of employees’ work time is wasted on inefficient communications and collaboration. This translates to an annual cost of more than $5 million in organizations with 500 employees. 

For many organizations, the lack of a standardized platform creates communication silos that hinder effective collaboration. But even if everyone is using the same tools, it’s impossible to know everything that goes on across the organization. The issue becomes more pronounced as organizations expand globally with increasing numbers of mobile and remote workers.

A team may launch a project not knowing that it’s a duplicative effort or that decisions made in another department have impacted the basic assumptions. In seeking to involve relevant stakeholders, the team may be unaware of experts who have significant knowledge of the topic. As the project progresses, multiple versions of numerous documents may accumulate while the team lacks crucial information needed to drive the project forward. 

Adding Context to Collaboration

AI tools could facilitate collaboration by monitoring, recording and transcribing voice and video communications, and capturing and indexing information stored in email and chat. This information could be correlated with data in HR, CRM and other enterprise applications to provide context and create an enterprise-wide view of available resources. 

Going back to the hypothetical team described above, it’s easy to see how AI-powered collaboration could help keep the project on track. Instead of guessing at the appropriate individuals to involve, the team could quickly identify the best people based on expertise. Relevant resources, both internal and external, could be gathered at the outset. The team could also uncover “tribal knowledge,” previous work that could benefit the project, and any issues that might affect the project’s assumptions, scope and timeline.

No such platform exists today but it’s far from the realm of science fiction. Organizations are already using AI chatbots to streamline contact center workflows. Chatbots can handle basic customer service requests and hand off to a human agent if the customer asks a question the chatbot can’t answer. But AI doesn’t end there — it continues to provide the agent with potential answers and other resources that could help the agent serve the customer. Similar techniques could be employed in the collaboration paradigm.

AI is poised to not only transform industry sectors but the way knowledge workers communicate and collaborate. Smart organizations should start thinking about applying AI in collaboration to increase productivity, facilitate projects and uncover new business opportunities.

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