The Three Stages of AI Adoption - Where are You?
Generative AI is transforming industries. Businesses are recognizing the value and potential of AI and are moving through stages of adoption to capitalize on its benefits. This blog post explores the four stages of generative AI adoption, from no adoption to the complete transformation of business functions, with a focus on the third stage and real-world examples of generative AI’s impact.
Stage 0: No Usage or Experimentation
Currently, most people and organizations are in this initial stage. Factors such as lack of awareness, limited opportunities, concerns about data privacy or regulation, or uncertainty about the return on investment might deter individuals from taking the plunge. However, as the technology rapidly evolves, maintaining this position will become increasingly unacceptable.
Stage 1: Individual Usage of GPT Tools such as ChatGPT, DALL-E, & Copilot
In the first stage of adoption, individual contributors within a company are experimenting with AI to enhance their individual productivity. These tools are being used in a wide array of applications, including content generation, software development, search, and data recall.
However, during this stage, there is no organizational alignment around standard usage and practices. There is little integration or automatic inclusion of context in these tools. This is a dangerous point in adoption; without clear guidelines and enterprise contracts with providers, there is a large opportunity for data leakage. Additionally, a lack of coordination can result in inconsistent application of AI tools and missed opportunities.
To address these issues, companies should:
- Establish clear guidelines, provide training and resources to help employees understand the capabilities, limitations, and threats of AI tools.
- Establish enterprise agreements with the providers of these tools to ensure your data is protected. Enable data privacy controls in ChatGPT. Sign up with Azure Cloud OpenAI access for better enterprise support. Copilot for Business has better data controls & protection.
- Encourage cross-functional collaboration and knowledge-sharing, allowing departments to learn from each other’s experiences and successes with AI.
Stage 2: Inclusion of Generative AI in Automated Workflows
As businesses progress through the stages of adoption, they begin integrating generative AI tools into their existing workflows. This integration either enables new areas of automation or increases the impact and personalization of existing automation. Easy opportunities that exist in almost every organization include automated summarization, translating unstructured data into structured data, entity resolution, language translation, and AI code review.
This integration is accomplished by adopting recently-launched tailored software tools and platforms or through the development of internal tools using APIs. Large organizations are already seeing significant performance improvements.
Automated Summarization
When was the last time you didn’t attend a meeting and intended to watch the recording, but never found the hour? Generative AI can be easily employed to create concise summaries of long form content. Easy-to-digest summaries can be created from lengthy such as:
- Meeting transcripts
- Long-running email threads and tickets
- Legal documents
- Product documentation
- Employee handbooks & benefit descriptions
Providing yourself and your team with summaries instead of requiring significant time to ingest information will improve cooperation, efficiency, and compliance. If you have team churn, it will help new members get up to speed and reduce organizational knowledge loss.
Translating Unstructured Information into Structured Data
Unstructured data refers to information that is not organized in a predefined manner, such as text documents, emails, images, or social media posts. Converting this data into a structured format allows this information to be consumed by existing platforms such as CRMs and project management software. Examples include:
- Automatically categorize and tag customer support tickets based on their content, enabling faster response times and more efficient resource allocation.
- Fill out customer templates in Salesforce based on email exchanges and notes from phone calls, saving sales team members time and paperwork.
- Automatically create tasks for the team based on meeting transcripts ensuring that valuable lessons don’t get lost in the shuffle.
Entity Resolution
Entity resolution involves identifying and linking records that represent the same entity across different data sources, such as customer databases or supplier lists. Generative AI can:
- Identify duplicate or inconsistent records in databases, helping businesses maintain accurate customer profiles, streamline communications, and avoid errors in billing or shipping.
- Link related entities in large datasets, enabling more comprehensive analysis and a deeper understanding of customer behavior and preferences.
Translation Services
While software-driven translation services have existed for a long time, large language models can be used to translate text or speech into different languages while preserving intent and tone at levels previous software has failed to achieve.
Automated translation that businesses can rely on provides a significantly lower barrier of entry to greater cultural understanding and can open new markets that were closed due to language barriers.
AI-based Code Reviews
AI-powered tools can review software code to identify bugs, vulnerabilities, and areas for improvement. This allows businesses to:
- Increase efficiency of high-salaried team members.
- Ensure that software meets security and performance standards, minimizing the risk of cyberattacks and system downtime.
Stage 3: The Future of Business — Generative AI Replaces Core Functions
The third stage of generative AI adoption is the most transformative, as AI begins to replace entire business functions or even core offerings. This stage represents a significant shift in the way businesses operate, enabling them to achieve extreme efficiency, cost savings, and scalability. This is what we’ve been promised for the last few months, but few have yet to achieve.
This level of integration has only been accessible to organizations with the resources to develop custom AI models, but the flexibility of newer GPT models is opening this world to groups of all sizes.
AI Designed Drugs
Pharmaceutical company GlaxoSmithKline (GSK) collaborated with AI firm Exscientia to discover new drug candidates using generative AI, and these have entered clinical trials. Investment in this field has skyrocketed in recent years.
AI in Fashion Design
Generative AI has also found its way into the fashion industry. Companies like H&M and Tommy Hilfiger have collaborated with IBM to develop an AI-driven design tool that analyzes customer preferences, sales data, and market trends to generate new product designs. This generative AI solution helps fashion brands stay ahead of the curve by quickly identifying and responding to changing consumer tastes, resulting in more relevant and appealing clothing lines.
AI-Generated Art
In the realm of art and creative content, generative AI has enabled the creation of entirely new works without human intervention. For example, the AI-powered art collective, Obvious, developed a piece called “Portrait of Edmond Belamy,” which was generated by a generative adversarial network (GAN). This AI-generated artwork was auctioned at Christie’s, a prestigious auction house, for $432,500, demonstrating the potential for generative AI to disrupt the art world and create new opportunities for artists and collectors alike.
AI in Legal Services
Generative AI has also been implemented in legal services, where it is used to draft and review legal documents. There are many solutions built for use by lawyers, and many organizations are re-evaluating their own legal needs and relationships as AI advances.
No matter your stage, Turing Strategies can help. Get in touch with us at turingstrategies.ai or by email at getstarted@turingstrategies.ai
