By: Ilana Jucha
Uncategorized 1 minute read

Is AI worth the hype? Yes!

December 3, 2021

In a 2020 survey on artificial intelligence (AI), McKinsey concluded the following:

  1. 50% of respondents say that their companies have already adopted AI successfully in at least one business function
  2. Organizations that adopt AI see a real value in terms of increased revenue and cost reductions on a functional level 
  3. Businesses that are seeing significant profit from AI adoption plan to invest more in the technology 
  4. This expansion in technology capabilities is likely to cause a greater gap between early AI adopters and companies that are falling behind in terms of technology adoption

Companies that are early to adopt AI will have a serious competitive advantage in the future business market. Data from MIT and BCG’s reports show that organizations have a 21% of becoming marketing leaders if they focus on the initial steps of AI adoption today. For organizations that entrench AI solutions into their organization, their chance rises to 39%. This number further increases to 73% for organizations that orchestrate full-scale adoption of AI now. 

Despite this glaring fact, some businesses are still considering whether AI is really worth the hype. 

In our line of business, we have seen many business executives skeptical about emerging data technologies and wondering whether these types of innovation can really be implemented correctly within their organizations. 

We often see that business executives like to take a wait-and-see approach to understand how the technology will mature and put the brakes on hiring talent until AI expertise is more readily available. As a result, these organizations prefer to be ‘fast followers’ rather than ‘early adopters’. 

This is a big mistake. AI systems take significant time to develop and implement. Machines need to accumulate a sustainable amount of data to build intelligence; simultaneously, organizations need time to get accustomed to new technologies. Ensuring that AI models integrate into your IT infrastructure is another major issue that requires serious time and planning. It is also important to consider the transition from piloting to implementation in production systems. 

In addition, as we have seen in our previous article on How to find the right talent to implement AI, the hiring pool for AI practitioners is tiny. 

The time to adopt AI is running out. Venturebeat estimates that companies have about 3 years left to adopt AI. How did they come to this calculation? Noting that futurists’ J curves predict innovations have a window of opportunity between 12-15 years – the period from which technology emerges to when it reaches across-the-board adoption – and that AI become popularized in between 2009 and 2012, the deadline set to adopt AI is approximately 2024. 

Organizations that decide to hold off on AI will be at a significant competitive disadvantage. So it is clear – the time to adopt AI is now. 

Prove the AI skeptics wrong 

What can you do to prove the skeptics wrong and start to implement AI today: 

Develop an AI vision: 

Define what AI looks for in your organization. While it is important to understand how your industry and competitors are adopting AI, start by pinpointing what areas your organization will benefit from AI. 

Set a roadmap

Define a clear roadmap for AI development, understanding how AI will fit your entire organization, and ensure that you effectively communicate this roadmap to your executive team. Understand who are the key players in your data science ecosystem. Remember, data science requires more than the support of a data scientist; it requires involving several key figures such as business leaders, SMEs, project managers, and developers. 

Collaborate and educate

Ensure you encourage collaborations across departments and functions to create a robust outlook for AI adoption. Educate your employees about what AI will mean for their roles and provide necessary training when needed. 

Understand your technology: 

Institute technology infrastructures can be a huge barrier to AI adoption. Start by understanding how you can implement cloud systems to help you overcome these infrastructural issues. As IT infrastructures require time to adapt to AI technologies, ensure that you undertake thorough planning of what this transformation will look like for your existing technologies.  

Final thoughts 

As a data science company, we are at the forefront of the AI industry. We have seen the fast rate at which organizations are adopting AI. However, at the same time, we are also seeing many organizations struggling in the process. 

While there are several barriers to AI adoption, the clear benefit from implementing these solutions are undisputed. AI represents unprecedented opportunities for businesses across various sectors.  

Looking to adopt AI into your organization, get in contact with us today.