How to kill any AI project – 8 easy and powerful ideas – Part II
There’s a subtle difference between running an AI in the lab and real-world execution. Each AI project encounters formidable challenges upon transitioning from a controlled to the unpredictable environment of practical implementation. In the first part of the #AIAdventures, we discussed the critical issues that often send an AI project to the siding – a melange of the data dilemma, software engineering challenges, and privacy and confidentiality issues.
But there’s more. I’d like to turn your attention to a fresh set of challenges that haunt AI implementations:
- Resistance to change (current (manual) processes are there for a reason!)
- Integration challenges (if we use AI, it has to be seamlessly integrated, no extra tooling!)
- Complexity and explainability (if we don’t understand it, we can’t/won’t use it!)
- Cost concerns (we won’t spend thousands just to get started)
Much like our initial exploration, we won’t just pinpoint the threats but will pave a way towards overcoming them. Let’s dissect these challenges, exposing their roots, and deriving the insights needed to free your next AI endeavor from skepticism and uncertainty.
1. Things are going well as they are – I don’t want another tool
Imagine encountering an inefficient corporate process. The symptoms can be manifold: Reliance on very few people, slowness, queues, unreliability, you name it. You have a solution, or could develop one and present your approach just to be told to mind your own business (of course, in a friendlier tone): if you walk through the steps of the process, each step can be very well done by a person, without making mistakes, and usually they are quickly finished. So why bother with automation? Also, many processes are not number-driven (the task or the data do not come as numbers in a spreadsheet but are buried in text). And more: Can you guarantee that your AI is always right? Does it cover the entire process? Can you show it right away? Every “no” to such questions reinforces the negative sentiment towards the “new approach”. Do not pass go, do not collect an AI team.
Revisit the inefficient process and the discussion about it: Chances are that there are steps in this process that can be automated quickly. What if you could demonstrate the new approach without a full AI project? Intrigued? Take a look at the following video in which semantha is used not only to highlight relevant passages in a document but also to extract (the then-structured) information from it. Watch the video (it’s only 79 seconds), then read on…
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So what do you do with the data within semantha? If the proven process works, why complicate it with another tool? I offer two answers. First, strategic evolution is key. Not everything has to be turned upside down to be revolutionized. Automate the grunt work and direct your team’s focus on the hard tasks. Second, adding semantha does not mean introducing a new tool. With an extensive API everything you see in the user interface – and more – can be used programmatically. Assuming that you’re not thinking about a pen-and-paper process, you can do that seamlessly. And about the 100% process replacement: sometimes this is not the best way to go anyways. Maintaining the strengths of your current processes and the expertise of your workforce, semantha offers enhancements that ease the inefficiency headache. Adopting AI with Semantha is not just a change but a purposeful evolution for future success of your organization.
2. ML, LMM, NLP, KG, … AI’s all just too complicated
Using a tool effectively requires a basic understanding of its workings to avoid misapplication. Whether it’s preparing data for classical machine learning or prompting a pre-built language model (assuring that it gives the correct answer in the right format every time), diving in without understanding can lead to wasted resources or, at worst, failure. While hands-on learning is valuable, it’s not always practical. (I have to admit though that you’ll learn a great deal when you play with the tech.)
But that is a truism and thus not very enlightening. Encountering this problem often involves (rightfully) cautious decision-makers. Even with a sound plan, your AI project can be canceled before it really starts due to a business focus on core operations of the business rather than on emerging IT trends. Moreover, your project’s ROI depends on the uncertain success of AI adoption and the project competes with initiatives that the decision-makers are more familiar with. It can feel like an uphill battle.
If you rely on a proven AI platform, it does not have to be like that. Such platforms support the adoption of AI techniques and explicitly guide the user through the steps needed from the sketchbook to production. semantha, for instance, simplifies knowledge base setup, allowing easy education through supplying a few examples to the library or the design of sophisticated knowledge graphs. Using the applications is easy for subject matter experts and for admins alike: Understanding how to set up and use semantha, and maintaining its knowledge is easy and transparent. Extensive training is not necessary. Calculating a ROI is simplified – as you can benchmark your AI solution from the get go, you can tell quickly if your plan can be put into practice.
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3. We won’t spend thousands just to get started
In the previous section, we touched on the unclear return on investment (ROI) of AI – or vice versa the total cost of ownership. A concern often tied to the perceived exorbitant implementation costs. Decision-makers may view AI as a risky financial commitment, even more so when considering expenses beyond the initial implementation: Allocating resources to train existing staff or hiring specialists can further strain budgets and tie up resources.
Upfront costs for AI implementation can concern decision-makers. Premier solutions offer cost-effective and flexible pricing. semantha’s incremental scaling approach allows a manageable start with a proof of concept minimizing resource impact. As you gain confidence and witness the benefits, you can seamlessly scale the application, optimizing resource allocation and avoiding undue pressure on your workforce or budget.
semantha ensures tangible ROI through enhanced efficiency and accuracy. With the increased productivity, it delivers real-world business value and offers transparent tools and metrics to quantify the impact on your bottom line.
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In the evolving landscape where technology meets practicality, we believe semantha can be a guiding force through these challenges, especially when it comes to unstructured data.
If our insights resonate with your AI aspirations, your next step is to witness firsthand how semantha can transform your processes. Beyond a mere blog post, the proof is in the pudding. And you can eat yours during a personal demo tailored to your unique needs.
The full set of features, including the library, awaits within every semantha subscription, offering unparalleled flexibility for each Co-Worker. Ready to embark on this journey with us? Connect with your dedicated semantha representative to explore the seamless integration of AI into your workflows. For those without an active subscription, schedule a meeting with our team to dive deeper into how semantha can turn unstructured data into valuable insights.
