Before we dive into this exciting topic, let's first clarify what generative AI (and later adaptive AI) actually is. Generative AI is a field of artificial intelligence that deals with the development of algorithms that can create new data. This can be text, images, music, computer code or other types of data. ChatGPT, for example, is a generative AI model that can generate text, translate languages, write creative content and answer questions in an informative way. The goal: Generative AI systems are designed to create new content.
Applications of generative AI in the corporate context
According to Gartner, this is just the beginning of what generative AI can offer us in the enterprise context. Gartner describes how the technology can support us in exciting areas such as drug development, materials science or even chip design in the future. But artificial intelligence also shines in less complicated disciplines, of course. Other possible applications are:
- Marketing and communication: Automated creation of texts, images, videos for campaigns and content. Personalisation of marketing content is particularly noteworthy here.
- Customer service: Chatbots, digital assistants and avatars with voice processing for personalised support.
- Sales: Analysis of data to optimise offers and increase sales. Personalised offers and recommendations.
- Finance: Automation of processes such as invoice processing, reporting, analytics. Risk assessment and fraud detection.
- HR: Automation of application processes, onboarding, training. Generation of job ads and interview questions.
- Production: Assistance systems for employees, e.g. in robotics. Optimisation and monitoring of manufacturing processes.
- IT: Automated code generation. Natural language interfaces for applications ("no-code AI").
- Research & development: Support for data analysis, design of experiments and interpretation of results.
- Legal: Automated creation of contracts and other documents. Research and case analysis.
- Medicine: Early detection of diseases, personalised therapies, intelligent diagnostic systems.
How AI is used in recruiting, by the way, we show in our previous article.
The transforming landscape for technology professionals
Furthermore, in our last article we answered the question: "Does AI create more jobs than it destroys?" To be successful in the new world of AI, we need a new skillset to work with this new technology and ensure that our talent is strengthened. Managers need to lead the way in this development and promote training and talent development. Vittorio Cretella, CIO of Procter & Gamble, agrees and sees AI not as a replacement for human talent, but as a augmentation of it. He goes on to say:
"Where humans will make the biggest difference is in problem definition. This is about breaking down a problem into key questions and identifying patterns before trying to find an algorithmic solution. We need executives and teams to focus on this stage to develop inquisitive skills and take enough time before moving on to solutions."
Just as humans can adapt (and that has driven our evolutionary development ever since), artificial intelligence can do the same - as so-called "adaptive AI". The goal: Adaptive AI systems are designed to adapt to new information, data or environments without having to be programmed or trained from scratch.
Adaptive AI thus refers to the ability of AI systems to adapt and learn from new data and situations. This means:
- Adaptive AI systems can learn from new data and situations and improve their performance over time.
- Adaptive AI enables faster decision-making and better resilience to interruptions.
- Companies that adopt adaptive AI practices are likely to outperform their competitors in terms of operational efficiency and innovation.
- Adaptive AI requires a shift in mindset and culture, as well as investment in new technologies and processes.
- AI engineering will play a critical role in the development and implementation of adaptive AI systems.
- Adaptive AI will enable new business models, products and services and break down „decision-making silos".
And to ensure that adaptive AI becomes essential for companies to remain competitive and resilient in the rapidly changing world. The technical evolution, so to speak.
Let's take a closer look at AI engineering in this context. It involves the design, development and deployment of AI algorithms, models and systems that can learn and adapt from new data and situations. AI engineering uses various techniques such as machine learning, deep learning and natural language processing to develop adaptive AI systems that can perform tasks such as image recognition, speech recognition and natural language processing.
Furthermore, it is also about integrating these systems into existing business processes and systems and ensuring that they are scalable, secure and reliable. In addition, AI engineering engineers work with data scientists and other stakeholders to identify business needs and opportunities for adaptive AI and develop strategies for implementing these systems in a way that adds value to the business.
It is important to note that functioning change management provides the breeding ground for AI engineering and thus also for adaptive AI.
Adaptive artificial intelligence and the industry
Adaptive AI will also come into play in all of the above-mentioned industries. Industry can also expect a leap in innovation:
- Healthcare: AI-powered diagnostic tools, personalised medicine, drug development and medical robotics are already being used to improve patient outcomes and optimise healthcare processes.
- Finance: AI-powered fraud detection, credit risk assessment, portfolio management and trading algorithms are being used to improve financial decision-making, reduce risk and optimise investment returns.
- Manufacturing: AI-powered predictive maintenance, quality control, and supply chain optimisation are being used to improve efficiency, reduce downtime, and increase productivity in manufacturing processes.
- Transportation: AI-powered autonomous vehicles, traffic management systems, and logistics optimization are being used to improve safety, reduce traffic congestion, and increase efficiency in transportation networks.
- Energy: AI-powered energy management systems, predictive maintenance, and energy efficiency optimization are being used to reduce energy consumption, improve grid resilience, and optimise renewable energy sources.
- Agriculture: AI-powered crop yield prediction, precision farming, and livestock monitoring are being used to improve crop yields, reduce waste, and optimise resource usage in agriculture.
- Cybersecurity: AI-powered intrusion detection, threat analysis, and incident response systems are being used to improve cybersecurity defences, detect and respond to threats more quickly, and reduce the risk of security breaches.
Speaking of cybersecurity: With such a strong intrusion of technology into our daily lives and work, the question of security naturally arises. And because of the power of this technology, it is particularly important that artificial intelligence is used safely and effectively.
After all, improper use can have serious consequences: AI can have a significant impact on individuals, the company, society and the environment. For example, AI systems can make decisions that affect people's lives, such as determining healthcare services or predicting crimes.
Furthermore, AI can and will be misused - namely to spread misinformation, promote prejudice and launch cyberattacks. Fake news and deepfakes are already commonplace. And the controversial election victory of Donald Trump in 2016 with the involvement of Cambridge Analytica was already 7 years ago - we cannot even imagine what could happen in the next US election in 2024.
Guidelines for the use of AI
Therefore, artificial intelligence needs ethical guidelines to ensure that AI is used responsibly. This includes ensuring that AI systems are transparent, explainable and fair. And that's the next challenge: because of the complexity, it requires a multidisciplinary approach. This includes involving experts from different fields such as law, ethics and sociology in the development and use of AI systems.
In addition, AI systems need to be continuously monitored to ensure that they function as intended. This includes monitoring for anomalies, bugs and security vulnerabilities. Last but not least, we need a culture of accountability to ensure that AI is used ethically. This includes challenging individuals and organisations to take responsibility for the impact of their AI systems.
Overall, then, we need to take a proactive approach to ensuring that AI is used for its intended purpose. The petition to pause AI development was a first step, but we need to continue to be proactive and critical in our approach to AI.
Automation & Job Displacement
As we stated in the last article, while generative AI will displace some jobs, it will create new employment opportunities in areas such as AI training, deployment and maintenance. Moreover, generative AI can increase human creativity and productivity, allowing people to focus on higher-value tasks that require human intuition and imagination. And that is much more fulfilling for us humans
Adaptive AI, on the other hand, has the potential to automate professions that require human adaptability, problem solving and decision making - that would be in customer service, healthcare and finance, among others.
Adaptive AI will displace jobs with repetitive tasks such as data entry, accounting and marketing. But it will also create new job opportunities in areas such as AI training, data analysis and decision-making.
A classic example: In customer service, adaptive AI can automate tasks such as answering frequently asked questions, routing customers to the appropriate departments and providing personalised recommendations. However, human customer care is still needed to handle complex questions that require empathy, creativity and human judgement.
Human after all
Despite the fact that artificial intelligence, whether generative or adaptive, is making a significant impact on the way we live and work, people are needed to understand this technology or to add our "human touch" to the work. Of course, it is important that we welcome AI with open arms to understand how it can help us - or even what challenges it brings. Because this sword is a powerful one. Even more powerful than the internet was back then.
It is crucial that individuals, businesses and governments work together to ensure that the benefits of AI are shared equitably, that employees are trained and prepared for the jobs of the future, and that AI is applied in a controlled domain (certainly a challenge). And that starts with the individual. If we understand what artificial intelligence can and cannot do, we can play to our individual strengths. And in the best case, compensate for our weaknesses.