We are in the midst of a massive AI hype cycle. As generative AI advancements have surpassed all expectations in the last few years, there have also been some AI rollouts within the tech industry that were not as effective as initially hoped. Deploying generative AI within organizations in an impactful way will require a layer of human intervention. The incorporation of human expertise limits the risk of hallucinations, ensures overall response accuracy, and enhances the security of user interactions. 

As the board and C-Suite become better versed in the capabilities of AI, they are mandating their operations and IT leaders to “deploy first, ask questions later”. However, speedy implementations are extremely risky without human supervision.

Looping in the human 

Until now, we have mostly seen generative AI and automation used as a means to pass off lower-impact tasks. It improves the efficiency and accuracy of responses for things like content moderation and generation, translating languages and customer service inquiries. As more enterprises get familiar with AI, we will inevitably witness the creation of new work types that are generally more complex than previously interpreted.

To win in today’s technology and business environment, organizations (regardless of industry or scale) will need to provide a distinct blend of solutions specific to certain verticals. These must also include a “human in the loop” that can complete complex customer inquiries in real time. Currently, users are leveraging the same large language models (LLMs): OpenAI’s GPT (Generative Pre-trained Transformer) series, Google’s BERT (Bidirectional Encoder Representations from Transformers), and Facebook’s RoBERTa (Robustly optimized BERT approach). While this generative AI adoption is great progress, the overall business landscape still sees hesitation in widely adopting the technology – especially in the United States. 

Only 3.8 percent of American businesses use AI to produce goods and services, according to the U.S. Census Bureau. This is a tell-tale sign that there are still some AI myths that are serving as a roadblock to companies making a complete investment in the expanding technology. 

Sorting through AI’s truths and myths 

Educating organizations about the realities and misconceptions of AI will depend heavily on IT decision-makers gaining support from their executive leadership teams. Part of that argument will be ensuring them that AI tools will augment current talent – not replace them. These solutions work to increase workflow, accuracy, and efficiency while freeing up key talent to do more impactful work as they relieve them from more mundane, manual tasks.

There is also a common misconception that AI will suddenly solve an organization’s business problems. The effectiveness of AI heavily depends on the technology’s ability to learn. This requires constant investments of time and repeated iterations of tasks before its value is truly realized. As companies focus their AI solutions on highly specific aspects of their processes, the requirement for human intervention is becoming more apparent than ever before.

We have witnessed this with major fintech leader MoneyLion. As one of the most prominent names in the FinTech industry, generative AI was playing a critical role in the growth of its sector as enhanced customer experiences quickly rose as a top business priority. By working with a BPO (business process outsourcing) provider, MoneyLion was able to utilize generative AI to amplify their customer service capabilities — but they did so by enabling the provider’s frontline teammates to respond quickly, accurately, and confidently to customer inquiries. 

By placing a human in the loop, MoneyLion’s customer service operation was able to utilize knowledge articles from its help center and understand and communicate with clients in natural languages. This resulted in a significant reduction in AHT (average handle time), an increase in overall customer satisfaction, and over 100,000 queries processed since the tool’s implementation. This is an authentic depiction of when a human-led AI strategy can yield high-impact results for an organization. 

To get the most out of their AI investments, businesses must pair the technology with their human talent. These team members not only build, QA, train, build, deploy, and refine these systems, but having a human in the loop is a critical component in preventing the mistakes driven by the technology’s hallucination. This eliminates key corporate risks while also defining the capabilities of the future enterprise.

Developing a human-led AI strategy

As any business enters the AI realm, a key learning point is that any tool you select will only be as effective as the data upon which it is trained. This makes a strong data collection strategy a must-have before implementing any AI-powered tool. Investing in a data warehousing solution is a solid option to collect, annotate and ensure all valuable company data is safe, secured and sorted all in one place. It is also important that any selected AI solution is both as industry- and business-model specific as possible (such as a generative AI chatbot to enhance customer service operations and the overall experience).

Thorough training and education will be essential for team members within your business who will interact directly with the AI solution. Whether it is through regular generative AI seminars or on-demand content and webinars, having resources available for the team to refer back to over time will be a key component of your human-driven AI strategy. 

When it comes to determining the AI tool’s effectiveness, collaborating with IT teams on internal KPIs will help keep both sides accountable. This could include regular quality checks on the accuracy of the AI generated responses, to how the chatbot is capturing data from a customer or client interaction. This can then inform future customer intervention practices and ensure the AI tool is delivering significant results.

As we seek to refine and enhance the way we work, AI has the greatest potential to spearhead this revolution in the technology and business landscape. Whether it yields the biggest returns or requires more education to ensure efficient, secure and consistent results, incorporating human intervention within the strategic AI process and rollout will future proof your organization for years to come. 

Bryce Maddock is the CEO and other founder of TaskUs Inc., a leading provider of outsourced digital services and next-generation customer experience.