By Ant Cousins, Director of Customer Success at ProFinda.
The business world is buzzing with terms like machine learning algorithms, Natural Language Processing (NLP) and sentiment analysis but these Artificial Intelligence or ‘AI’ tools are often focused on consumer facing products and services. So how can they help Internal Comms? Here’s 7 ways AI-powered collaboration platforms can make your life easier:
- No more blank profiles. “Sure, I’d be happy to fill in another profile”. Said no employee ever. If they’re forced to fill in skills profiles for their appraisal you might get the bare minimum to ‘tick the box’. But with just a few bits of data about each employee, and a lot of employees, we can use AI to predict the skills and knowledge. This means we can ask closed, but intelligent, questions like ‘do you know project management?’ which always gets a better response than ‘tell us what you know?’.
- No more noise. Current social methods of connecting staff through groups and communities etc. rely upon employees finding the right groups, those groups being active enough to keep their attention and them seeing the right update at the right time. With AI we can ‘engineer serendipity’ between the right employees at the right time using matching algorithms. This ensures every conversation fixes a business problem and reduces the community management overhead of promoting, pruning and curating groups and content.
- No more social stigma. The use of social networks and forums mean employees are just as able to share pictures of their cats as they are to collaborate on a business problem. This can cause problems getting senior leaders to use, or support the use, of social tools. With the added relevance of an AI powered platform there is less need for social sharing and a clearer focus on work outcomes for each engagement. Tools like NLP and sentiment analysis can also prove that the content being shared is work related.
- Clearer ROI. With so much luck involved in the connections made between people we often rely on reporting engagement stats as a form of ROI. This assumes if employees use it, it must be useful. But with the ability to like, share and comment comes the ability to conduct a lot of activity not directly attributable to a business benefit. With AI, engineered connections are more closely linked with business problems and NLP combined with sentiment analysis can provide reports on what’s being shared with who and why.
- On-demand. Employees, especially millennials, are used to services on-demand in their personal lives and they don’t drop that expectation in the office, so keeping them happy with Internal Comms is only going to get harder. With AI, machine learning algorithms can deliver the right content to the right people at the right time in the right way by analysing their activity and predicting what will engage them most. The increased efficiency and relevance of connections on-demand can also lead to millions in efficiency savings.
- Employee Engagement. It’s hard to make a link between the annual employee engagement survey and anything but the largest of business changes. With AI you can use sentiment analysis and analytics to track the real-time engagement of employees across the company at a more granular level. This enables a much more accurate measurement of your comms impact and, with time, allows you to predict the engagement of employees based on trend analysis.
- Less guessing. An experienced internal communicator will know the likely impact of a particular change or announcement on the engagement or culture of their company, but what if you’re new to the company, or new to Internal Comms? How do you offer strategic advice to the business on the likely impact of an internal story? With AI and predictive analytics you can, over time, predict the impact on employee engagement based on trend analysis. So… evidence based guessing!