Considering implementing AI in the workplace? You’re not alone. As AI continues to become more powerful, more businesses are convinced that they’ll fail without it. In fact, according to this report from Accenture, 75% of executives fear going out of business within five years if they fail to scale AI now.
AI is advancing rapidly, and it makes sense that CEOs and business leaders want to capitalise on the technology now. However, as with any new technology, it’s important to carefully consider the potential challenges and drawbacks before implementation.
What assurances are there for accuracy and accountability?
Likely the biggest challenge with AI powered by Large Language Models (LLMs) at the moment is a lack of accuracy due to the phenomena of hallucination. Many AI programs have caused public scandal due to inaccurate information, with sources found to be completely made up. Most recently, Deloitte had to refund part of a $440,000 government report because multiple errors were found, including fake academic references and a made-up quote from a Federal Court judgment. There’s also the case of SaaStr, whose founder revealed that an AI coding assistant went rogue and wiped a database, then lied about it.
These cautionary tales are important to be aware of when investigating any new AI software. Ask questions about what data the AI was trained on, how likely mistakes are, and how information can be verified. If a business is implementing its own AI system, it will need to constantly obtain large volumes of fresh, high-quality anddiverse data to train the system – but this data needs to be obtained, cleaned, and checked for accuracy, which isn’t cheap.
Will it improve the customer experience?
If you’ve ever been stuck in a loop with an AI chatbot, frustrated and wishing you could speak to a real person, you’ll know how customers feel when AI isn’t working effectively. Any new AI solution needs to be tested from a customer experience perspective first. If the process incorporating AI can’t achieve a result that’s at least as good as the process without it, then it’s likely to only harm your brand’s reputation and lose customers. On the other hand, when AI solutions like chatbots work well, customers get the answers they need more quickly. You just need to determine what will be the most effective solution for your customers.
Is an AI solution aligned with your business strategy?
Before introducing an AI system into your company, consider whether it will help your business achieve its long-term goals. If you implement AI without a clear plan or understanding of how it will impact your business in the long-run, it’s far less likely to deliver ROI. The AI solution should integrate seamlessly with current processes, whether that’s automation, making customer experiences better, or using data to fuel better decisions. AI is not a quick fix – think ahead, and with the right consideration, it can be a crucial tool for business growth.
Do you have the team and resources in place to implement AI in your organisation?
Implementing any new tool or system into your business is typically a complex process. Integrating AI is no different. You’ll have to assess existing IT infrastructure to determine whether you have the computing power and storage capacity to accommodate an AI system. If you don’t have this, it may require costly upgrades or switching to a cloud-based third party solution – potentially requiring integration of an overhaul of your existing IT system. On top of this, you’ll also need to ensure you have the right people to implement it. That could look like hiring new talent, upskilling your current teams, or investing in continual training as the technology evolves.
What are the financial costs of implementing AI in your business?
LLMs are still a fairly new technology, so AI solutions driven by them can be expensive. The cost of training, integrating, testing and operating these systems must be considered upfront to determine whether it will provide appropriate ROI. The upside of implementing these cutting edge tools is that while upfront costs can be daunting, in the long-term, the automation of repetitive, time-consuming tasks and giving staff more time to focus on more important tasks can allow for higher profit margins.
Just consider the total cost of implementing AI before jumping in. Think about hardware, software, talent acquisition, ongoing training and maintenance – all big upfront and ongoing costs, but over time, you may find that an AI solution is the more economical option.
The decision to implement AI in your business isn’t a quick or easy one. It requires careful consideration around accuracy of the data, customer experience, goal alignment, and whether you have the team to implement it – or the funds to do so.