How to put Artificial Intelligence to work

This article is a continuing series on fields gaining on automation and artificial intelligence. Today’s topic is about the strategic implementation of AI within the organization space.  download article

In previous posts, we talked about AI in general and its impacts on specific industries. This article is about AI implementation.

bubble model of Corporate AI Governance

AI Governance

Organizations confine themselves to a set of regulations that maintains control of the collective. The collective in the AI-based arena is comprised of people, AI-enhanced computers, and AI-based machines. Although AI-enhanced computers and machines can perform systematic processes, they lack the emotional and social context that binds organizations.

“AI governance is an overarching framework that manages an organization’s use of AI with a large set of processes, methodologies, and tools. It aims to enable organizations to take full advantage of AI while minimizing costs and risks. Here are some key principles and benefits of AI governance: Key Principles of AI Governance:

  • Ensuring effective use of AI
  • Risk management
  • Regulatory compliance
  • Ethical usage of AI

Benefits of AI Governance:

  • Ensures responsible use of AI
  • Promotes public trust within the AI systems and technologies
  • Empowers organizations to function with complete trust and agility instead of slowing them down
  • Helps organizations monitor, manage, and control all artificial intelligence activities

Organizations must ensure that AI systems respect and comply with ethical standards, regulatory requirements, and risk management frameworks. They should establish a clear strategy for using AI and guidelines for collecting and managing data. It’s important to note the distinction between AI governance and AI regulation. While AI regulation refers to the laws and rules made by a government or regulator regarding AI that apply to all organizations that fall under their purview, AI governance instead refers to how AI is managed in an organization.“  [1]  [2]  [3]  [4]  [5]

AI-based Organizational Work

The question on everyone’s mind is how to use the AI-based computer to do the grunt work while people can be productive in the creative areas.

To put AI to work, organizations need to adopt a strategy for its integration.  AI-based processes use a combination of big data and computers. The transition involves understanding how to use data and AI-based computers according to imposed regulations.

Using Data

The implementation of AI-based machines is gaining momentum at an exponential rate. Consider why Tesla is collecting vast amounts of road driving data. To be the leader in AI-based cars, the neural network needs to learn from real data regarding how to respond to immediate driving conditions.

Since AI is data-driven, there are a plethora of free data sources to feed the algorithms.

AI Applied

AI-based organizational tools are becoming increasingly available- most require little to no programming

Automation Platforms:

  1. Decisions
  2. InRule
  3. Appian
  4. OutSystems
  5. Pega Platform
  6. ServiceNow
  7. IBM Decision Manager Open Edition
  8. UiPath Automation Platform
  9. Kissflow Inc
  10. Agiloft Inc
  11. Pipefy Inc
  12. Ultimus Inc
  13. Caspio
  14. GW Apps
  16. Joget DX

Productivity tools

  1. A project management tool that uses AI to help manage product development processes.
  2. An AI-powered tool that generates content ideas and helps with copywriting.
  3. Adobe Express: An AI-based design tool that helps create graphics, videos, and web pages.
  4. An AI-powered HR tool that helps with employee engagement and retention.
  5. SurferSEO: An AI-based SEO tool that helps optimize website content.
  6. Futurenda: An AI-powered scheduling tool that helps manage appointments and meetings.

Psychology of implementation

The role of AI in organizations is a 24/7 worker doing the grunt work to free up human’s more creative work. How we get along is by understanding the strengths and weaknesses of humans and AI-based machines.

Humans are intuitive, emotional, and culturally sensitive. [1]

AI-based machines are fast, more accurate, and consistently rational.  However, machines do not have a social context. They do not understand why we do what we do. What they understand is rules- rules based on laws and accepted practices. But they don’t understand the human condition that merited the rules and many of the gray areas that make us function as a collective group.

Employees may relate to AI apps like an intelligent virtual partner coexisting in the workspace. Tactically, you can have several collaborating computers as in a think tank. Wherein each computer acts as a virtual member of the team. AI-based collaboration is a new trend in the workplace.

In conclusion, AI is an enabling technology where awareness of its advantages is on a trajectory.

To Top

Leave a Comment

Your email address will not be published.