Enterprise Connect 2017 conference coverage
Reporting and analysis from IT events
Artificial intelligence and machine learning are two of the biggest topics in computing right now. AI typically...
represents the broad concept of computers carrying out their own, autonomous tasks, using machine learning as a means to gain knowledge to make better decisions.
AI services and machine learning can cross over into unified communications and collaboration to improve the ability of workers to manage and share information. Organizations can apply machine learning to discover how employees interact -- either ad hoc or around a specific project -- and then apply intelligence to improve collaboration.
Consider, for example, the scenario of Jane and Bob working together on a project. As part of their efforts, they collaborate in the development of a proposal and a customer deliverable. Today, when Jane and Bob have their weekly status calls with the members of their team, they must manually compile the information they need to share on the call in advance.
With AI services, some intelligent process would have discovered the relevant documents based on past information and interactions, and have them ready for the meeting. Taking it a step further, one could easily envision a future where workers use bots or natural language queries to Siri or Amazon Echo to gather the information they need before calls or for projects.
Optimizing customer service interactions
Here's another potential scenario: Jane receives a call or text message from Bob. The AI engine displays their past written communications, documents they've collaborated on and perhaps relevant information from a customer relationship management or ERP platform. This enables Jane and Bob to have the information they need at the ready, rather than searching for it.
Most of the early investments in AI services are focused on optimizing customer interaction workflows, such as streamlining order processing or having intelligent bots recognize a likely topic of a customer inquiry and respond quickly with necessary information.
For example, IBM and Salesforce recently announced a partnership to combine IBM's Watson with Salesforce's Einstein to better optimize customer sales and service engagements. These sorts of initiatives should put better information into the hands of customer service representatives to improve customer engagement.
AI tools flirt with collaboration workflows
On the UC front, we're still in the early stages of bringing the power of AI services to real-time collaboration. The last year, though, has seen numerous partnership announcements to advance AI services into the world of collaboration.
In June 2016, for instance, Cisco and IBM announced an agreement to integrate IBM Watson, Verse and Connections with Cisco Spark. Potential services could involve integrating Watson into collaborative sessions to handle associated tasks and workflows.
At its Ignite conference in September 2016, Microsoft highlighted ways it is looking to use its Cortana voice interface to manage interperson communications. Similar to the Cisco-IBM approach, Cortana could potentially serve as a virtual assistant for engagements, handling tasks, bringing required information into view and enabling natural language queries of data stores. For example, "Cortana, show us the sales report for the second quarter."
At this point, IT leaders should have discussions with their collaboration and enterprise software vendors to understand roadmaps and partnerships. While AI services might not yet be ready to improve collaboration, we're not far off from their launch. Companies that can quickly leverage AI to improve internal and external collaboration and communications will have an edge over companies that delay.
AI systems benefit businesses in three key ways.
Businesses need to understand how AI can be deployed.
AI chatbots target human-based tasks.