Scaling Gen AI: Why Getting it Right Matters

Call it what you want, but the buzz of Generative AI (Gen AI) has reached dizzying heights in the last few years. Many companies have seized this opportunity to create their own Gen AI pilots. Gen AI is a type of artificial intelligence (AI) that can replicate and produce content like text, code, and even images.

The Path to Scale Starts With a Good Pilot

Most organizations now find that, at the pilot level, this technology has led to great results. But, advancing beyond the pilot has proven very challenging. Gen AI can only be as successful so far as it can recognize the brand’s personality and be aware of any internal changes. Platforms such as Starmind aid the “learning and unlearning process” to ensure effective scaling by providing the collaborative connection between Large Language Models (LLMs) and human-verified information. Starmind's AI-powered Expertise Directory integrates with your company's own Generative AI platforms, enabling instant human verification for business-critical questions. 

McKinsey & Company takes this notion of failing to scale Gen AI further by saying we have reached the end of the “honeymoon phase”, as only 11% of companies have adopted Gen AI at scale. To keep this excitement surrounding Gen AI alive we must build scalable Gen AI. We can’t waste the hard work done in the pilot phase. It’s vital for long-term success and ROI. 

Does Your LLM Speak Your Language?

Furthermore, there is another potential setback for businesses that they may not have considered: the deployment of Gen AI. Companies worldwide develop unique internal dictionaries, conveying ideas distinctly, and exuding their brand character. This means that a Gen AI LLM will not include the company's 'language'. Add to this the fact that an astonishing 80% of company information is not written down but is found in the minds of people within the company. This suggests that the LLM becomes less accessible and as a result, less likely to yield fruitful results. 

Empower Your Humans

So what’s the solution? Get your people involved. From the ground up to the CEO level, everyone must be a part of the process to ensure that scaling is effective and fructiferous. “No company can outsource its way to digital excellence”, therefore ensuring that your team is involved with new processes is a sure way to secure your success in the future. But do not panic, this does not mean increasing your talent pool. It means focusing on the talent you have and that they have access to becoming the best they need to be.

Quality Assure Your LLM With Human Verification

Yes, using Gen AI does save time, and you can ask questions in real time. But, what if that information is erroneous? Does the response fail to address your inquiry directly and accurately?  What if the LLM has been fed garbage in the first place? Unreliable answers only hinder the scaling of Gen AI further as trust is eroded and doubts creep in.

Starmind’s CEO, Marc Vontobel says to mitigate the risk of inaccuracies with your internal GPT model, you must only work with quality data, and have your answer verified by an actual human. Then, thanks to human-verified insights you can say goodbye to fruitless searches and useless information. This ensures your Gen AI’s output is accurate, relevant and up-to-date.

Minimize Inaccuracy Risks in Your Generative AI

Imagine inviting experts to weigh in on questions or to quell those nagging doubts you have with a question you’ve asked, Starmind, does exactly that. Integrating human insight eliminates errors and recovers lost search time effectively. In essence, this means that your internal Gen AI and the human beings at your company need to join forces to ensure the success of these systems, and their users. It’s not just about having access to data; it’s about having access to the right data.

Involving people at all points, from start to use, is a sure way to scale your AI and increase productivity. Gen AI must be a priority throughout the company, with all departments working together to allow a healthy symbiotic relationship to flourish. 

A Case Study: Mondelez

Scaling AI has revolutionized R&D in the CPG industry, as Starmind has helped teams in global companies such as Mondelez by speeding up R&D, boosting efficiency, saving costs and streamlining operations by disseminating critical knowledge swiftly. Mondelez has seen “tangible benefits” since working with Starmind, take a deeper look at the Mondelez case study here. Scaling Gen AI in your organization is the engine to build agility, drive innovation, and enable growth, ultimately ensuring you can outpace your competitors.