By Arkady Sandler
Utilizing artificial intelligence (AI) in business operations is a reliable way to boost the speed, efficiency and overall quality of work, and 81% of employees already believe that AI has improved their job performance. In fact, according to SnapLogic, 68% are ready for their employers to deploy more AI-based tools.
The global AI market is currently worth over $136 billion, and its value is projected to skyrocket over 13 times this number over the next seven years, which means we are only seeing the beginning of what it can do for companies. However, while AI has enormous potential and widespread acceptance by those in the workforce, it still has limitations that prevent humans from relying on it entirely.
Here are a few tips to help your organization avoid three of the most common pitfalls that arise when using AI technology in business operations.
How to successfully incorporate AI in the workplace
1. Make sure your results are unique and relevant
Remember that AI relies on the inputs it is given and the data it is trained on to produce results. Because of this, it is always possible that the results generated are too generic to be effective without further refinement.
Currently, AI has been implemented by at least 35% of businesses in their operations, according to the IBM Global AI Adoption Index, while 42% of companies say they are actively exploring AI integration. The primary applications identified by these participants include chatbots and automated email chains. Consequently, emphasizing personalization and delivering unique outcomes has become increasingly vital, as the customer experience now wields a direct influence on your brand’s long-term success.
For instance, if your marketing team uses GPT to generate text without finalizing the outputs or maintaining a focus on tailoring the message to your target audience, not only will your customers be unhappy with a generic experience, but you will be more likely to see a decline in business because your voice will no longer stand out from your competitors.
2. Beware of inaccurate, incomplete, or unintentionally biased outputs
AI’s ability to contextualize information is much more rudimentary than a trained human mind. It is also important to remember that an undertrained predictive model becomes a “self-fulfilling prophecy” of deteriorating results becoming worse over time. For instance, if your own previous predictions cause the data stream to change, AI must be able to account for this, or its outputs will become increasingly less useful. This means that it is more likely to return an inaccurate, irrelevant, or incomplete result if a query is not carefully or explicitly worded.
Universal AI literacy is something the global community must embrace in order to fully realize the potential of AI, but this is especially important for businesses. Teaching employees and users the importance of high-quality data and how to navigate the blind spots artificial intelligence might have is the best way to reduce the likelihood of problems stemming from inaccurate results.
A possible instance of this would be using virtual assistants in a healthcare setting to help streamline the diagnostic process for basic urgent care needs. Imagine telling an AI diagnostic tool that you are experiencing kidney pain. Based on that input, the AI would be likely to prescribe kidney-specific treatments. However, if you were to simply complain of pain in your lower left side, it would likely recommend additional diagnostic tests to help pinpoint the source of the pain, which might not be the kidneys at all.
To help mitigate this, it’s essential to educate everyone potentially using your AI about its limitations. Understanding how to ask the best questions to get optimal, helpful answers is a skill that can be learned, and acknowledging that there may be biased or inaccurate results opens the door for critical thinking and overall improvements in how your business uses artificial intelligence.
3. Remember that AI is constantly evolving and needs upkeep
It is natural and expected for artificial intelligence systems to degrade over time. In the same way that you must upgrade company software on a schedule or purchase new office furniture periodically, your business needs to plan for regular maintenance of its AI tools.
Regular system updates help keep your AI system performing at its peak effectiveness and reduce the likelihood of poor or erroneous outputs. For example, using a prediction system to manage resources based on a particular data stream is an excellent way to boost efficiency.
However, without consistent updates and pretraining, it is possible that the system would not account for its own impact on the current data, such as mentioned earlier with an under-trained predictive model getting stuck in a cycle of deteriorating outputs. This would lead to increasingly less accurate information as the system degrades until the whole thing becomes nearly unusable.
Finally, it is important to bear in mind that, in many cases, artificial intelligence needs further training specific to an organization before it can be truly effective. Routinely examining the data it has been trained on and ensuring it’s as complete, clean, and neutral as possible will make upkeep a much simpler, more efficient task.
Your people are your best tool for better AI incorporation
Ultimately, the companies that can find the ideal balance of human and robot collaboration are the ones most likely to see success. The truth is that while artificial intelligence has grown by leaps and bounds, it is nowhere near ready to replace humans who can think creatively and provide valuable context to make AI outputs useful, relevant, and unique to your brand.
Sci-fi movies have embedded a fantasy in our minds that the goal is to have everything automated or done by completely autonomous robots. This blind spot on our part has been responsible for plenty of failed attempts at integrating AI into society. Instead, we need to recognize the strengths and weaknesses of the tech and take time to build up autonomy in the right way. This is the only path we have to a future where humans, robots, and AI coexist successfully.
FAQs about incorporating AI in the workplace
What are the problems with AI in the workplace?
It can give rise to issues such as inaccurate results, dull information, outdated data, and more. It is crucial to bear in mind that a hybrid approach, combining human expertise with AI capabilities, is necessary instead of solely relying on AI.
What is an example of AI in the workplace?
AI can be utilized for minor tasks like composing emails, distributing letters, or running advertising campaigns. Additionally, AI can serve as the core concept of a business, powering devices that address market challenges through intelligent solutions.
How does AI positively impact the workplace?
Tasks that were previously time-consuming can now be completed more quickly, freeing up valuable time for individuals. Moreover, this collaboration opens new possibilities for the creation of additional job roles and the optimization of workplace organization. It’s clear that AI will have a profound impact on all business processes related to information and document management.
About the Author
Post by: Arkady Sandler
Arkady Sandler is a serial entrepreneur and technology executive with over 20 years of experience. He founded five startups, successfully exiting three of them. He is an expert in AI, product innovation, effective product management, and technology development, and can talk about the current state of AI and its future, automation and digitalization, product innovation, and robotics.
Company: Docet TI
Website: www.docet.ai
Connect with me on LinkedIn.
Originally published at All Business Technology