Cloud Wars
  • Home
  • Top 10
  • CW Minute
  • CW Podcast
  • Categories
    • AI and Copilots
    • Innovation & Leadership
    • Cybersecurity
    • Data
  • Member Resources
    • Cloud Wars AI Agent
    • Digital Summits
    • Guidebooks
    • Reports
  • About Us
    • Our Story
    • Tech Analysts
    • Marketing Services
  • Summit NA
  • Dynamics Communities
  • Ask Copilot
Twitter Instagram
  • Summit NA
  • Dynamics Communities
  • AI Copilot Summit NA
  • Ask Cloud Wars
Twitter LinkedIn
Cloud Wars
  • Home
  • Top 10
  • CW Minute
  • CW Podcast
  • Categories
    • AI and CopilotsWelcome to the Acceleration Economy AI Index, a weekly segment where we cover the most important recent news in AI innovation, funding, and solutions in under 10 minutes. Our goal is to get you up to speed – the same speed AI innovation is taking place nowadays – and prepare you for that upcoming customer call, board meeting, or conversation with your colleague.
    • Innovation & Leadership
    • CybersecurityThe practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks.
    • Data
  • Member Resources
    • Cloud Wars AI Agent
    • Digital Summits
    • Guidebooks
    • Reports
  • About Us
    • Our Story
    • Tech Analysts
    • Marketing Services
    • Login / Register
Cloud Wars
    • Login / Register
Home » AI Myths Debunked: Benefits and Limitation of Artificial Intelligence in Business Applications
AI and Copilots

AI Myths Debunked: Benefits and Limitation of Artificial Intelligence in Business Applications

Bridget CourneyaBy Bridget CourneyaMay 17, 2021Updated:May 28, 20217 Mins Read
Facebook Twitter LinkedIn Email
Share
Facebook Twitter LinkedIn Email

Artificial intelligence continues to play an ever-increasing role in the workplace, whether it’s handling mundane job tasks or making an impact on how people work. Applications of artificial intelligence are found throughout many organizations, as Gartner predicts that AI will be one of the driving forces behind infrastructure decisions by 2025. However, numerous myths about AI exist, which makes it more challenging to convince stakeholders to implement this technology. Education is key to eliminating these myths and helping businesses fully take advantage of AI in the workplace.

 

AI Myths Debunked

Understanding the various benefits and limitations of artificial intelligence is essential for CIOs due to the variety of AI myths behind this technology. Businesses need to understand the full capacity of AI to avoid confusion while also utilizing this technology to provide the best business value. Knowing the many benefits of artificial intelligence can help companies maximize productivity and efficiency in today’s ultra-competitive work environment.

 

Here is an overview of common AI myths and how your business can benefit from using this innovative technology.

 

Myth #1 – We Don’t Need to Develop an AI Strategy

Many companies don’t understand the advantages of using artificial intelligence in business. A lack of understanding of the benefits of artificial intelligence is a significant roadblock that puts them at a disadvantage to competitors utilizing this technology.

 

CIOs can fully take advantage of AI by combining business priorities with opportunities to use the power of AI to augment human tasks. Businesses can begin this process by using AI to handle critical functions, such as the automation of administrative duties to save time and make it easier to focus on innovation. Frequently revisiting your company’s approach to AI is also important to maximize efficiency and ensure everything is working smoothly.

 

Myth #2 – AI is a Luxury During COVID-19

Another widespread myth is that artificial intelligence technology is a luxury for businesses trying to survive amidst the COVID-19 pandemic. However, nearly 25% of businesses are increasing their investments in AI technology to better meet the challenges of COVID-19, according to a recent Gartner pool.

 

Artificial intelligence has especially been critical for government and healthcare organizations trying to predict the spread of the virus, which allows them to better manage emergency resources. Businesses are also using artificial intelligence software to quicken their recovery efforts by reducing costs and creating business continuity plans to limit the impact of disruptions from COVID-19.

 

While AI technology can’t fix everything, many organizations realize the benefits of AI in overcoming the immediate and long-term challenges of the pandemic. The role of the CIO is to proactively look at ways AI can improve business operations, such as processing data faster and augmenting the decision-making process today and also in a post-pandemic world.

 

Myth #3 – AI is Only About Creating Algorithms

Creating and applying machine learning algorithms to develop a predictive model is usually the least challenging aspect of an AI project. One of the biggest problems is making sure that enough data is gathered to ensure the problem being solved by AI technology is well-defined, as deployment is often the most difficult stage during an AI project. Many IT leaders are unable to transition AI predictive projects beyond proof of concept due to these significant challenges.

 

CIOs need to reach out to stakeholders to discuss how to define a specific business problem that can be resolved with the help of AI technology. Organizing the business process, tools, and managing the employees in advance can help ensure the testing and deployment process goes much smoother to maximize the chance for success. Understanding the limitations of artificial intelligence is helpful in overcoming these problems, as artificial intelligence is much more than creating algorithms.

 

Myth #4 – Artificial Intelligence and Machine Learning are the Same

Artificial intelligence is a broad term for categorizing engineering techniques by computers. On the other hand, machine learning is an extensive subfield within artificial intelligence, as these machines can learn without the need for programming. Machine learning is often effective for solving a specific task by recognizing data patterns, as many companies use machine learning to determine if an email is legitimate or if it’s spam.

 

However, it’s important to realize that machine learning isn’t the same as deep learning. Deep learning is another form of machine learning that’s resulted in many amazing breakthroughs, but it’s not always the best technology for handling all types of problems. In fact, a lot of the current problems in the workplace can be solved by using traditional machine learning or rule-based systems.

 

Using the latest artificial intelligence software isn’t always the most efficient way to handle business problems. Data scientists need to analyze artificial intelligence as a whole to implement the best solutions to align with business goals. Combining deep learning and other artificial intelligence techniques are often recommended for handling complex problems that require more human insights.

 

CIOs need to clarify these various terms while discussing artificial intelligence with stakeholders. Breaking down terminology into specific techniques is often an effective way to show how this innovative technology can solve real-world issues in the workplace.

 

Myth #5 – AI Will Only Replace Mundane Job Tasks

Artificial intelligence technology is often thought of as replacing mundane job duties, which saves time and makes it easier for employees to focus on more important tasks. While artificial intelligence software has the potential to automate these simple tasks, it can also accomplish higher-value tasks. For example, AI can analyze thousands of legal documents in minutes by extracting useful information much quicker and with fewer errors compared to lawyers.

 

CIOs can look at ways to take advantage of artificial intelligence technology by identifying activities that can either be automated or augmented by AI, whether it’s related to customer service or project management. Employees can be retrained to work more efficiently with the help of artificial intelligence software. Remaining transparent and communicating about the use of artificial intelligence in business is essential to reducing negative sentiment while also helping employees prepare for these changes in the workplace.

 

Myth #6 – Black-Box AI Needs to Always Comply with Rules and Regulations

An AI system that inputs and processes information hidden from users is known as “black-box AI.” The rules involving black-box AI are often dependent on a variety of factors, such as security, privacy, digital ethics, and transparency with customers. 

 

Typically, AI that creates insights for internal usage doesn’t need additional explainability. On the other hand, AI that involves making decisions about people will require explainability, such as determining eligibility for credit or loans. An even higher requirement of explainability is required for AI-making decisions that result in significant consequences, such as autonomous driving due to ethical and potentially legal reasons.

 

CIOs need to ensure that applications of artificial intelligence comply with existing regulations to avoid any legal issues. Providing support for your testing and validation team is also critical in gathering enough information to determine the level of explainability needed for an AI application.

 

Final Thoughts

Understanding the different benefits and limitations of artificial intelligence is essential for businesses to fully take advantage of this technology. Many AI myths remain prevalent throughout the workplace, which makes it more difficult to invest in AI. Taking the time to educate yourself and dispel these myths with your employees can make the transition process of using AI technology much easier. Artificial intelligence in business will continue to increase and play a vital role in the workplace, as now is one of the best times to begin planning for these changes.

Related DAC Content

The Role of AI Within Low-Code Development

Artificial Intelligence in Legal Services: Are we creating “AI-ttorneys?”

Back @ IT: What You Should and Shouldn’t Be Automating

Artificial Intelligence Ethics and Dangers: How to Handle AI Concerns

Vertical Cloud Industries, RPA, Technical Debt and a New AI CAGR Forecast

Dynamics 365 CE / CRM Dynamics Business Central / NAV Dynamics GP Dynamics SL Power Platform
Share. Facebook Twitter LinkedIn Email
Bridget Courneya
  • LinkedIn

Bridget is the Founding Editor of Acceleration Economy and drives a multi-faceted editorial strategy towards the organizational mission - to empower businesses to compete in the Acceleration Economy through application of tech + human ingenuity. With a heart for the tech community and a mind for agile organizational change, her Analyst POV covers Business Psychology and IT Strategy. Bridget embraces her passions of social impact, diversity and inclusion by leading the Analyst Network and Women in Tech initiatives.

Related Posts

Snowflake Expands AI Data Cloud to Revolutionize Automotive Manufacturing and Data Integration

May 14, 2025

Arvind Krishna’s Next IBM Miracle

May 13, 2025

Arvind Krishna Restoring IBM to Former Glory

May 13, 2025

Apps Apocalypse: Bill McDermott Joins Satya Nadella in Saying AI Agents Will Crush Applications

May 12, 2025
Add A Comment

Comments are closed.

Recent Posts
  • Snowflake Expands AI Data Cloud to Revolutionize Automotive Manufacturing and Data Integration
  • Arvind Krishna’s Next IBM Miracle
  • ServiceNow Takes Major Steps Toward ‘Operating System of the Enterprise’ Destiny
  • Arvind Krishna Restoring IBM to Former Glory
  • Apps Apocalypse: Bill McDermott Joins Satya Nadella in Saying AI Agents Will Crush Applications

  • Ask Cloud Wars AI Agent
  • Tech Guidebooks
  • Industry Reports
  • Newsletters

Join Today

Most Popular Guidebooks

Accelerating GenAI Impact: From POC to Production Success

November 1, 2024

ExFlow from SignUp Software: Streamlining Dynamics 365 Finance & Operations and Business Central with AP Automation

September 10, 2024

Delivering on the Promise of Multicloud | How to Realize Multicloud’s Full Potential While Addressing Challenges

July 19, 2024

Zero Trust Network Access | A CISO Guidebook

February 1, 2024

Advertisement
Cloud Wars
Twitter LinkedIn
  • Home
  • About Us
  • Privacy Policy
  • Get In Touch
  • Marketing Services
  • Do not sell my information
© 2025 Cloud Wars.

Type above and press Enter to search. Press Esc to cancel.

  • Login
Forgot Password?
Lost your password? Please enter your username or email address. You will receive a link to create a new password via email.