What is Artificial Intelligence?
Artificial Intelligence, or AI, is a field of technology that gives machines the ability to do things that would normally require human interaction or intelligence. Tasks such as solving problems, making decisions, and recognizing patterns can easily be accomplished through AI. Unlike traditional software that simply follows programmed instructions, AI systems can adjust their behavior and improve over time.
For most organizations, AI is no longer just a fancy tool in their rack; it has become a driver of efficiency and innovation. When used properly and responsibly, its benefits to business can be extremely significant, including streamlining business operations and improving customer engagement.
What are the key branches of AI?
AI has been widely used across industries even before the boom of generative AI chatbots in 2022. Below are three of the most commonly used branches:
Machine Learning (ML)
Machine learning works by using algorithms that learn from historical data. It uses the behavioral patterns of users to refine its performance without needing to be reprogrammed. One familiar example of ML is how streaming platforms can curate show recommendations based on a user’s viewing habits.
Natural Language Processing (NLP)
From the name itself, NLP allows machines to interpret and generate human language in a way that feels natural. This has been well applied in business chatbots that handle customer inquiries to apps that translate languages in real time. ChatGPT and Google’s Gemini, which are powered by generative AI, are a more advanced type of NLP.
Robotic Process Automation (RPA)
RPA is focused on automating routine, rule-based tasks. As such, it is especially popular in business operations, like data entry, invoice handling, and form completion. Through RPA, organizations can reduce administrative workload, speed up operations, and minimize mistakes that often occur in manual processes.
What is AI governance?
AI governance refers to the policies, structures, and ethical standards that guide how AI is developed and applied within an organization. Its purpose is to ensure that AI systems are transparent, fair, and accountable.
The goals of AI governance include:
- Aligning AI with both organizational and societal values.
- Encouraging openness about how AI tools work and make decisions.
- Minimizing risks of bias, misuse, or discrimination.
- Meeting legal and regulatory requirements.
For a more in-depth explanation, read this article on responsible AI adoption in boardrooms.
What are the advantages and disadvantages of using AI?
There are good and bad things about using AI. Here are some of the benefits it has brought:
- Streamlined repetitive work: Gives users more time to do more important things.
- Accelerated insights: Analyzes large datasets quickly, giving decision-makers useful information faster.
- Stronger decision-making: Provides predictive models and simulations to guide business strategies.
- Reduced errors: Improves accuracy by minimizing manual handling of data and processes.
- Constant availability: Offers around-the-clock customer service or system monitoring.
But while AI adoption is growing rapidly, organizations must also prepare for its challenges:
- Data risks: AI systems are trained and depend on vast datasets, which could be vulnerable to bias, manipulation, or cyberattacks. This is why protecting data quality and security is crucial.
- Model risks: Attackers may attempt to steal or tamper with AI models, altering their behavior or reducing their accuracy.
- Operational risks: Over time, AI models can drift from their original performance, develop biases, or break down without proper oversight.
- Ethical and legal risks: Poorly designed AI can lead to unfair outcomes, privacy violations, or non-compliance with regulations. For example, using biased data in hiring systems could unintentionally favor one demographic group over another.