Three Phases of AI Adoption and its Impact on Digital Investigations

Discover the three stages of AI adoption and its implications for digital investigations. Cellebrite’s AI tools offer powerful insights in an AI-driven world.

The hype around artificial intelligence (AI) has led to an increase in discussions about how AI will transform our lives. However, while the buzz is new, AI as a concept has been around since the 1950s and it already exists in the products and services that we use every day.

For example, Netflix offers personalized recommendations. Apple’s Siri serves as a personal, virtual assistant. And self-driving cars use AI algorithms to navigate and make real-time decisions.

Augmented reality driver dashboard – Source: Shutterstock

Experts predict that 10% of vehicles worldwide will be driverless by 2030. Companies across all industries understand the substantial value of integrating this technology into their offerings and internal operations, recognizing the extensive benefits it provides for their customers and workforces.

Basically, the current use of the term AI refers to computer systems that can perform tasks that typically require human intelligence, such as learning from experience, understanding natural language, recognizing patterns, and making decisions.

This brings us to what the hype today is all about – Generative AI.

The Rise of Generative AI (Gen AI)

Generative AI tools use a subset of AI called machine learning. Machine learning focuses on using algorithms and compute-intensive systems that allow computers to learn from large training datasets without being explicitly programmed. This is called “model training” and it allows the computer to make predictions and decisions, just like humans learn from experience.

Generative AI tools use a subset of AI called machine learning – Source: Cellebrite

Large language models (LLM) are trained on massive amounts of text that include articles, books, websites, and more. During the training period, LLMs process billions of words and phrases to learn patterns and relationships between them, allowing the models to generate human-like responses to prompts.

Tech giants Microsoft and Google both released their respective AI chatbots Bing Chat and Bard. The most widely used, ChatGPT from OpenAI, launched in late November 2022 and according to Statista, the AI-powered language model gained 1 million users within the first five days.

Only two months later it reached 100 million monthly active users in January 2023. Contrast that to the Internet, which reached the same number of users approximately 7 years after it was made available to the public.

Cellebrite Anticipates the Trend

At Cellebrite, we recognized long ago the inevitable shift toward incorporating AI into our products and services.

For example, Cellebrite’s investigative analytics solution, Pathfinder, comes built-in with features such as image and video classification, facial recognition, media similarity, language-model-based chat topic detection, and optical character recognition (OCR).

Cellebrite Pathfinder Dashboard with Image Classification – Source: Cellebrite

As AI continues to evolve and become even more sophisticated, we will see it go through the three distinct phases that all transformative technologies undergo: pre-transition, transition, and post-transition. These stages describe the evolution, adoption, and maturity of a particular technology.

Pre-transition phase of new technology adoption

How many of us remember what life was like before the Internet existed?

Accessing the Internet today is as simple as clicking the browser icon on your mobile or computer device and you are instantly connected to the world. In the late 1990s, household phone lines were used to dial up to connect to the Internet and the user was forced to wait minutes for the connection to load.

The pre-transition phase is marked by the emergence of new technology with limited awareness and adoption. Innovators and early adopters begin to explore and experiment with the technology’s capabilities.

During this phase, companies engage in research and development, prototyping, and testing to build the technology’s core concepts and functionalities.

Growing Interest During the Transition Phase

During the transition phase, the technology attracts more users and businesses. Adoption rates increase, and the technology becomes more recognizable within the industry and among consumers.

This growing recognition incentivizes companies to focus on refining the technology based on user feedback and scaling up production to meet growing demand.

According to McKinsey & Company, gen AI is experiencing a breakout year. The McKinsey Global Survey found that 79% of all respondents have had at least some exposure to gen AI, either for work or outside of work.

New technology takes time to develop, test, and implement as there are often challenges involved.

Firstly, creating robust infrastructure is a complex process that takes time and costs a significant amount of money. Large language models (LLMs) require a huge amount of computing power for training, maintenance, and daily use.

CNBC reports that Microsoft’s Bing AI chatbot, which is powered by the ChatGPT model, needs at least $4 billion of infrastructure to generate responses for all Bing users.

Also, agencies and institutions may react slowly to new technology. Continuous learning and integration of technological improvements are fundamental to fully utilize its unparalleled abilities.

Post-transition phase of new technology adoption

The post-transition phase encompasses widespread adoption. During this phase, the technology is quickly becoming an integral part, of business operations and everyday life. So much so, that it becomes a transparent infrastructure.

AI Infrastructure Illustration – Source: Shutterstock

The focus shifts from rapid growth to optimizing efficiency, enhancing user experiences, and further expansion through updates and innovations. In the case of AI, we see that it is quickly becoming the foundational infrastructure that new industries and businesses will be built upon.

The Internet transformed industries and created entirely new areas of opportunities for businesses and people. Social media, e-commerce, and mobile applications would not exist without the infrastructure of the Internet.

The growing role of AI

In the same way, AI will continue to advance and play a more prominent role in our lives, especially because we can certainly harness the power of AI to build better products and services.

For Cellebrite, AI sits at the center of our infrastructure – enabling the development of more dynamic features, as well as easy and quick updates and innovations to our offerings.

This becomes increasingly important as the amount of digital evidence grows exponentially.

The widespread adoption of the Internet was good for business, but it also led to new forms of crime as well. The Internet Crime Complaint Center (IC3) website saw a significant increase of over 800,000 complaints between 2000 and 2022.

As AI continues to develop, it too becomes an avenue for criminals to exploit. Law enforcement agencies must be ready to tackle AI-enabled crimes.

Faster Investigations with AI

Automated image categorization is one example of how AI is already helping investigators uncover leads and reduce time-to-evidence.

Image classification AI algorithms can automatically categorize images based on predefined criteria, helping investigators prioritize their review by focusing only on images relevant to the case.

For example, Cellebrite Pathfinder can automatically analyze and consolidate media files into 35 different categories, such as Drugs, Money, or custom categories created by a user.

Tools like Cellebrite Pathfinder allow investigators to easily analyze and process necessary video data using AI media analytics (Credit: Cellebrite)

Additionally, automated OCR technology converts text within images or scanned documents into machine-readable text that can be searched and analyzed further.

Finally, Pathfinder’s topic detection feature helps summarize and extract the main subjects or discussions from a collection of textual-based communications, which can unveil hidden connections and patterns in communication.

AI-Powered Digital Forensics

Agencies today face serious challenges conducting comprehensive investigations from start to finish. Digital forensic experts are flooded with large volumes of complex data, which is impossible to review manually.

AI offers unprecedented capabilities that will empower users by saving time and allowing greater control over the investigative process, thus enabling faster case resolution.

With AI, investigators can identify and uncover important evidence at the start of the investigation, allowing them to analyze case data faster and surface important insights sooner.

We recognize that agencies need the most sophisticated technological resources to access actionable insights and resolve cases faster. Cellebrite is committed to the development and education of cutting-edge analytical tools to assist agencies throughout the digital investigative process.

To find out more about Cellebrite’s Digital Intelligence Suite of Solutions, contact us today.

Key Takeaways

Think differently.

Continuous learning and integration of technological improvements are fundamental to fully utilizing AI’s unparalleled abilities.

Plan differently.

During the pre-transition phase, agencies should engage in research and development, experimenting with AI solutions to understand their potential.
The transition phase involves refining tools based on user feedback and scaling up their use, indicating the need for planning scalability and user training.
In the post-transition phase, agencies should focus on optimizing efficiency and further expansion through updates and innovations, requiring strategic planning for long-term integration of AI technologies.

Act differently.

Digital investigation agencies must adopt AI-powered solutions for faster and more effective investigations. Automated image categorization, text analysis, and topic detection provided by AI-powered solutions like Cellebrite’s Pathfinder can help investigators uncover leads and patterns in communication more efficiently.

By leveraging AI, agencies can prioritize relevant data, accelerate the investigative process, and surface critical insights early in the case. Agencies should actively invest in AI technologies to enhance their investigative capabilities and adapt to the evolving landscape of AI-enabled crime.