AI, Training Technology

3 Best Practices for Using Deep Learning AI

Yesterday’s post detailed what deep-learning artificial intelligence (AI) is, as well as its benefits and drawbacks for learning and development (L&D) professionals. Today’s post will cover more information about how you can implement deep-learning AI and upcoming trends.

learning

Source: chombosan / iStock / Getty

1. Research Tools

Do your research and select the AI-driven tools that are ideal for your specific organization, its goals, and its learners. Many systems and software out there will already have deep-learning AI integrated into them.

However, they may still not be ideal for your specific organization. Always make sure the deep-learning AI your systems use is implemented with your specific learners and organization in mind.

2. Rely on Big Data

You will need to rely on data from everywhere—from your website, from your sales department, from your learning management system (LMS), from your HR system, from your marketplace, etc.—to be able to take full advantage of what deep-learning AI can do. So, you’ll want to build a big data strategy and then integrate your organization’s systems to store and analyze data for its learners.

Essentially, you’ll want your deep-learning AI to be able to detect things like what your learners need to learn for your organization to remain competitive and when they need to learn it, as well as to monitor and address what your learners are interested in learning. And so on.

3. Be Realistic and Track Progress

Remember that deep-learning AI still needs to be implemented and monitored by humans if it’s to remain effective. And it can never be completely automated … at least, not yet.

So, as you implement deep-learning AI for your L&D plans and strategies, make sure it’s still meeting specific and achievable organizational objectives and that it’s continuing to make your learners more engaged and competitive. Deep-learning AI should never end up automating frivolous training programs or lead to worse knowledge retention rates, for example.

Deep-Learning Trends That Will Dominate 2019

According to Analytics Insight, here are five deep-learning trends that will dominate 2019:

  1. Training data sets bias will influence AI, but data scientists will work to combat this.
  2. AI will rise amongst business and society and will become a more prominent part of everyday life.
  3. More AI innovations and solutions will be funded and created to respond to real-life human problems.
  4. Audit trails will become more prevalent and will further explain the nitty-gritty behind how deep-learning AI reaches a conclusion.
  5. AI innovations will be built on cloud adoption capabilities.

Keep the information outlined above and in yesterday’s post in mind as you implement deep-learning AI if you want it to remain effective.