In November 2022, the OpenAI research laboratory released ChatGPT, a Generative AI Chatbot that can comprehend and generate human-like text, capable of producing novel and realistic content.

This release moved artificial intelligence into the mainstream, capturing the imagination of many around the world.

The “hype” associated with Generative AI has triggered the usual polarising series of public commentary, with some groups positioning artificial intelligence as the world’s saviour, whilst others see it as an existential threat.

To better understand the realities, it is important to remember that artificial intelligence is not new.

The origins of artificial intelligence date back to the early 1900s, with the first discussions regarding the viability of creating artificial humans. Today, artificial intelligence is an embedded part of daily life, used by billions of individuals every day to support a wide range of tasks (selecting music, getting directions, etc.)

However, up to now, artificial intelligence has been a silent companion, usually embedded as a backing service, not immediately obvious to the individual using it. Individuals working with artificial intelligence directly were usually experts within a given domain, with specific expertise and experience.

Generative AI services like ChatGPT changed this equation, allowing anyone to directly interact with artificial intelligence using natural language (no specific expertise or experience required). This paradigm shift dramatically broadens the viable audience, whilst also making the use of artificial intelligence self-evident.

In short, artificial intelligence has been on a 120+ year journey, with the most recent chapter covering the transformer deep learning architecture first proposed in 2017, leading to the inevitable release of ChatGPT in 2022.

  • Is this an important milestone for artificial intelligence? yes!
  • Are the machines rising, as seen in movies such as The Terminator? No.

I am not stating that there is no risk associated with artificial intelligence. As with any technology, it can (and will) be used for good and bad.

However, as it stands today, I believe the opportunities associated with artificial intelligence far outweigh the risks. This is especially true for enterprise businesses, who are under continuous pressure to optimise their value chain, whilst innovating to unlock new customer experiences and business models.

Therefore, I have identified four opportunities and four risks that I believe are most relevant (today) for enterprise businesses considering the use of artificial intelligence.

Opportunities

Data Insights:

  • Artificial intelligence can analyse large datasets quickly, consistently and cost-effectively, identifying patterns, trends, and correlations that would be impossible for a human to recognise. These insights promote data-driven decisions, whilst predicting outcomes that inform business strategies across the value chain.

Productivity Acceleration:

  • Artificial intelligence enables the automation of repetitive and common tasks, reducing the risk of human errors, whilst empowering every individual to maximize their potential. This leads to increased efficiency, effectiveness, engagement (moral) and cost savings.

New Customer Experiences:

  • Artificial intelligence can power always-available, personalised customer experiences, maximising go-to-market strategies, whilst improving engagement, response times and overall satisfaction.

New Digital/Data Business Models:

  • Artificial intelligence can act as the catalyst and facilitate the creation of new digital/data business models, potentially unlocking new monetisation opportunities.

Risks

Competition:

  • Artificial intelligence has the potential to disrupt traditional business models, powering new customer experiences and unlocking transformative digital/data business models. Businesses that fail to adapt risk becoming obsolete.

Information Protection:

  • Artificial intelligence is reliant on data, potentially including data that is categorised as sensitive. Data used or produced by artificial intelligence must be appropriately collected, stored, processed, managed and controlled.

Information Accuracy:

  • Artificial intelligence may misrepresent information with insights/content that appear convincing but may be incomplete, inaccurate, or inappropriate. This can be due to poor-quality training data and/or bias/manipulation. All insights/content must be verified by an accountable party.

Appropriate Use:

  • The use of artificial intelligence can have ethical, legal, and societal implications, covering consent, fairness, compliance, intellectual property, and the potential for unintended consequences. The use of artificial intelligence must be a conscious decision, focused on the intended outcome and engaged stakeholders.

Conclusion

I am extremely excited about the future of artificial intelligence. In the context of enterprise business, I believe artificial intelligence is primed to trigger the next wave of digital innovation, unlocking opportunities to disrupt and transform industries.

Therefore, although businesses must consider the risks associated with information protection, accuracy and appropriate use, I believe the biggest risk is not embracing the technology. Businesses that fail to do so, risk becoming obsolete.

enterprise architecture ea enterprise_architecture artificial_intelligence ai machine_learning ml generative_ai large_language_model llm natural_language_processing nlp transformer data prompt_engineering openai chatgpt gpt microsoft bing copilot google lamda palm palm2 bard sidekick stanford_alpaca koala gpt-j hugging_face risk_management information_security security cybersecurity lifeinwork