Transform Your Operations: The AI Advantage

Article by David K.

"Everyone talks about AI nowadays. I want to use it, but I don't know where and how!" – CEO of a midsize corporation (end of 2022)

The developments and possibilities in the field of artificial intelligence (AI) have been advancing so rapidly for years that it's increasingly difficult to keep track, let alone integrate AI into existing processes. On one hand, there's the challenge of juggling day-to-day operations, and on the other, pushing forward with digitalization within the company, ideally bringing it to a successful completion. Why should you take on yet another "latest trend"?

AI Creates Breathing Room. AI Realizes Potential.

AI not only provides short- and long-term breathing room but can also open doors we weren't even aware existed. Beyond technological possibilities, it saves valuable resources and allows for targeted scaling. AI has long surpassed the status of a "trend," and we're just beginning to reap the fruits of decades of research and development.

You might be wondering, "Why now?" By now, enough experience has been gathered with AI in various application fields to bring such projects to success. At the same time, it's not too late to keep your company competitive through AI integration. You've arrived at just the right time to transform digitally with low risk and benefit from extensive expertise. This article aims to give you a rough overview of where to start, what to look for, and perhaps even spark your first ideas.

What is AI?

Defining AI uniformly is no trivial task, and we don't want to presume to do so. However, we can comfortably lean on Elaine Rich's definition:

"Any computer program that can perform one or more tasks better and faster than a human is artificial intelligence."

Generally, three types of AI are distinguished:

1. General AI: The most widely disseminated idea of AI by pop culture is the "general AI," which would exhibit intelligence comparable to that of a human and thus possess broad problem-solving capabilities.
2. Artificial Superintelligence: An enhancement of general AI, artificial superintelligence would surpass humans in every way and is often used in dystopian science fiction.
3. Narrow AI: This is what we encounter in everyday life. Narrow AI is designed and/or trained for specific tasks, ranging from search and recommendation algorithms to facial recognition and robot vacuum cleaners.

A subcategory of AI is "Machine Learning," where an algorithm learns from data and, for example, can recognize patterns. It is differentiated into "Supervised Learning," "Unsupervised Learning," and "Reinforcement Learning."

• Supervised Learning: Models are trained on data that has already been labeled. A trained model can be applied to new data that resembles the training data to a certain degree, making it particularly useful for transferring expert knowledge into a model.
• Unsupervised Learning: This involves processing the available data without a training phase, making it particularly useful for exploration without bias.
• Reinforcement Learning: Used in robotics and gaming, the model starts relatively uninformed and learns through interactions with the environment.

The most significant technological advancements have been achieved through "Deep Learning," which processes vast amounts of data and can recognize much more complex patterns. Although these algorithms have been known for quite some time, computationally intensive training only became feasible with better hardware (e.g., powerful graphics cards). Thanks to deep learning, we now have the latest AI tools, including powerful chatbots (Large Language Models), image, and video creators.

Where Do I Start?

You've already taken the first and most important step: you're educating yourself about AI and are evidently looking to kickstart or elevate your digital transformation, automation strategy, or productivity enhancement. To identify initial starting points, consider these questions:

• Which processes consume the most time?
• Which tasks or processes are still handled manually?
• Are there large datasets that could potentially train an AI model?
• Would access to certain (new) data sources be helpful?
• For which tasks would partial automation already be beneficial?
• Which tasks definitely require employee involvement (e.g., to take responsibility for decisions)?

By now, it's clear in some application areas what AI tools can successfully manage and where the limitations still lie. However, new areas where AI can be applied are constantly emerging, although it's not always clear how much can be automated to full satisfaction. This also depends on individual company requirements. In such cases, a "proof-of-concept" (PoC) can be useful. A PoC allows you to test the possibilities and success of an AI tool on a smaller scale, such as for a simplified process or a representative subcategory. Although a PoC is sometimes seen as a risk investment, the potential savings in the overall picture offer significant added value. This allows for better estimation of individual developments in project planning and uncovering possible unknowns. Additionally, the developments are always usable for the larger follow-up project.

What Are My Options?

Once the most urgent pain points are clear, the next step is to identify which processes can be profitably and quickly automated. Understanding some of the possibilities that AI tools offer can help with this. Here, we'll focus on a few selected methods on a higher level that could be relevant for digital transformation:

Unlocking Data Sources

• Object Character Recognition (OCR): Read texts from scanned documents/PDFs
• Web Scraping/Crawling: Search websites for content and extract relevant information
• Intelligent Sensors: Capture environmental data in various forms

Cleansing

• Anonymization: Remove/replace sensitive content from texts or images
• Sanity Check: Remove data irrelevant to the task

Analysis

• Information Retrieval: Extract relevant information from texts
• Object Recognition: Recognize desired components in images
• Classification: Categorize documents, images, or texts

Prediction

• Make predictions about future developments from time series data
• Determine the (lack of) success of a process based on all components

What Could the End Product Look Like?

AI tools and methods can be implemented in various ways. The goal is to integrate them into ongoing processes and individual steps with as little disruption as possible, connecting to existing interfaces. Depending on the requirements, the following options are common:

Direct Integration:

• Integration into your existing infrastructure
• Mature algorithms or fully trained models are directly connected to your interfaces
• No graphical interface and little to no human supervision

Web Application:

• A graphical interface in the browser, available over the internet or intranet
• The application can run on a cloud (e.g., Google Cloud, AWS) or your IT infrastructure

Monitoring System:

• An "alarm system" that notifies with relevant information when certain events occur or just before they happen

Software:

• A standalone product that runs locally on any computer and includes the AI components

How Can It Continue?

Potential employees with expertise in AI are unfortunately very rare in today's job market. We recommend initial external consultation to assess feasibility and define your individual goals and requirements, including brainstorming the potentials within your company. Based on this, a functioning product (or PoC) can be created in no time, delivering the desired added value in the short and medium term.

Additionally, internal communication within the company becomes essential to create awareness and acceptance of a new AI tool. In digital transformation and automation, the initial impulse from employees is often that their job is at risk. Fortunately, this fear is usually unfounded. Experience shows that employees are even relieved when labor-intensive, previously unscalable processes are automated or simplified, allowing them to focus on more exciting tasks.

Have we piqued your interest? We're just scratching the surface here and would love to meet you for a first introduction.

At Deepsight, we're ready to help you navigate the complexities of AI and elevate your business processes. Whether you're just starting your digital transformation journey or looking to enhance your existing systems, our team of experts is here to guide you every step of the way.

Get in touch with us today to discuss how we can help you leverage the power of AI:

• Phone: +49 (0) 541 9313 2090
• Email: hi@deepsight.de

Let's work together to unlock new opportunities and drive your business forward. Fill out our contact form or reach out directly to schedule a consultation. We look forward to partnering with you on your AI journey!