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Applied AI

How a People-Centered Approach to Artificial Intelligence can Help you Optimize Your Workforce

An important new weapon in the war for talent is AI. This initialism is generally taken to mean “artificial intelligence,” but in fact it can refer to many different variations of artificial intelligence:

  • “Assisted Intelligence” – as used in chatbots and smart speakers
  • “Autonomous Intelligence” – as in self-driving cars, and
  • – “Augmented Intelligence” – which takes huge data sets and applies techniques like machine learning, cognitive simulation, natural language processing, fuzzy logic to this data to produce valuable insight
We believe recruitment of permanent and contingent talent is too important to be left to machines alone. In fact, research has shown that machine learning without human intervention not only fails to eliminate bias in talent evaluation, but may even increase bias over time.
Our “augmented intelligence” approach to AI, on the other hand, applies advanced techniques to support and augment human activities by sifting quickly through masses of connected data to understand concepts and infer meaning so that our systems can better respond to a human user’s inquiry. Meanwhile, machine learning accumulates more contextual knowledge with each conversation.

Enlisting an “Army of AI”


To realize our vision of how AI can create a better user experience, we employ an “Army of AI” strategy. This simply means that we combine the artificial intelligence capabilities of strategic, well-respected partners, including Brightfield, Opening.io, and IBM Watson, with our own internal capabilities to ensure we’re embedding the most accurate and most impactful insights and capabilities into our software.
At the heart of our internal AI platform is the Beeline Knowledge Graph.
A Knowledge Graph platform treats all of an enterprise’s data as an actionable asset and as a whole. By combining a Knowledge Toolkit with a Graph Database, it is possible to manage enterprise data in full generality. By structuring data in this way we can extract, query, analyze, and re-use enterprise data to generate insights that can augment and enhance decision making.

 

“AI should be about educating, not removing, decisions. Within 10 years, 90% of companies will collect all non-employees in one AI-powered system. You can get a head start if you act now.”

Colleen Tiner, Beeline SVP of Strategy

Unlock the Power of Your Workforce Data


The value proposition of a Knowledge Graph for the enterprise is that all data, data sources, and databases of every type can be represented and operationalized by the Knowledge Graph. The object is to perform all kinds of analysis with ALL – or any part – of the data.

To do this at scale requires artificial intelligence. By applying AI tools like cognitive simulation, fuzzy logic, machine learning, natural language processing, and other techniques, we can use Graph methods to:
  • Create better job descriptions
  • Identify qualified candidates more accurately
  • Select applicants most likely to complete their assignments successfully

Is a VMS Right for You? Then You Need the Right VMS.

For most energy companies, human capital expenses constitute the largest single cost of doing business. Your executives are concerned with ensuring that you can provide the top-tier talent they need to compete and succeed in an on-demand world.

Having an appropriate contingent workforce gives your company the flexibility to reduce the fixed cost of a full-time, expensive bench of talent in times of low productivity. Beeline VMS automates your contingent talent acquisition and management processes to ensure that you can confidently deliver the right contractors and contingent workers – at the right time, the right place, and the right price – to fit each specific situation.