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From the meaningless phrase in the nineties of “leveraging the power of the internet” and the dotcom boom to companies renaming themselves to include the word blockchain to boost their share price by 394%, the hype cycle surrounding tech is a familiar tale.
Fast-forward to the present day and the glory days of blockchain and cryptocurrencies are now in the rearview mirror as AI takes center stage. The names and tech may change, but again companies make misleading claims or exaggerating their AI capabilities.
Welcome to the dark underworld of “AI Washing,” where salespeople can be found in boardrooms making groundless AI-related claims in their sales pitches.
The practice has already appeared on the U.S. Securities and Exchange Commission (SEC) radar, but how can you protect your business from misleading claims, perhaps even outright lies, about new AI-driven products and services?
Key Takeaways
- Tech hype cycles have evolved from dotcom and blockchain booms to AI exaggerations.
- “AI Washing” involves companies making baseless AI claims to boost sales and reputation.
- Businesses must scrutinize AI vendors to avoid falling for misleading AI capabilities.
- Transparency, ethics, and accountability are crucial in evaluating AI solutions.
- Continuous support and updates are essential for effective AI implementation and ROI.
Protecting Your Business from Misleading AI Claims
In recent years, we have seen startups add a chatbot to their product or service that claims it uses AI when it doesn’t. One of the biggest AI washing scandals of the year was the accusations that Amazon’s AI-powered “Just Walk Out” technology, which allows users to pick their items and then leave, was also reliant on 1,000 workers in India, who manually checked almost three-quarters of the transactions than AI.
Amazon quickly dismissed the claims as erroneous, but the AI washing claims were already causing reputational damage. So, how can you protect your business from misleading AI claims?
Effective Strategies for Vendor Selection
AI already plays a crucial role in your business without you realizing it, whether through automated marketing campaigns, cross-selling, admin tasks, or aspects of the recruitment process.
However, AI is only as good as the data used to train machine learning algorithms. Humans must verify the data and remove any unconscious bias from the process. Choosing a vendor is no different, and your teams, with their inherent BS detector and unwillingness to take a vendor at face value, will be your best defense.
A quick search online will also lead to the door of other businesses that have already implemented the solution. Online reviews on everything from Google to Trustpilot will give you an early indication of whether they match what your organization is looking for. However, you can be even more proactive by contacting known customers to ease any concerns by asking questions about the vendor’s reliability, security, and ethical approach.
Transparency, Ethics, and Vendor Accountability
A concerning number of AI projects involve a complex decision-making process that humans cannot understand. They are left with a sinister ‘black box’ that enhances biases and produces errors in logic, but nobody knows why — meaning there is no accountability.
For these reasons alone, transparency and explainability should be at the foundations of your AI investment, especially if you are in a highly regulated industry.
Your shortlist of vendors should be able to share how their AI models, algorithms, and decision-making processes work and how they arrive at their conclusions without trying to baffle you with science. Only then can stakeholders determine whether they can understand precisely how it arrives at its conclusions and trust every output.
Maximizing ROI with Scalable and Integrative AI Solutions
Chances are you are dipping your toes into the uncharted AI waters for the first time, but you need to think beyond this first project. During economic uncertainty, every tech project is scrutinized for business value, tangible benefits, and ROI. The adage “You can’t improve what you don’t measure” has never been more critical.
From the outset, ensure the vendor provides metrics and KPIs of the problems their AI solves. Depending on your industry and business goals, such as reducing costs, increasing revenue, or improving customer experience and productivity.
Rather than risk adding to your organization’s rising technical debt, you need to understand how this new AI solution integrates with your existing processes, workflows, and tools and whether it could provide value to other departments in the business.
Stay aware of the trap of moving fast and breaking things. You must have one eye on the future and determine how this AI solution will evolve and scale while meeting your business’s needs. Ultimately, the success of your AI investment will be judged by its measurable impact, and your vendor must be able to articulate this from the outset.
Do not step directly into a live environment when ready to deploy your models. Pilot projects will allow you to test the AIs in tightly controlled environments that will let you evaluate their real-world efficacy and make adjustments before wider deployment.
Finally, remember that AI is a journey, not a destination. AI systems require continuing adjustments and improvement in response to performance feedback. Therefore, any agreement with an AI vendor must have continuous support and provision for regular updates if functional improvement is desired.
The Bottom Line
Whenever you hear about a new AI product or service, look closer and ask the right questions to help you determine if it’s the deal or more AI hype of exaggerated claims. In the same way you approach a phishing email or any online scam, if something appears too bad to be good, trust your gut and approach with extreme caution.
AI should not replace people; those who make this sacrifice will lose in the long run. Success requires humans and AI to work seamlessly together to complete tasks and goals that neither can accomplish alone. So lean on your human skills and curious mind by asking questions and digging deeper into the claims made by AI vendors.
