Augment and Compress: Leveraging AI for Maximum Business Impact
According to McKinsey, 71% of companies are prioritizing investments in AI, recognizing its potential to transform their business models and accelerate value creation. While AI is not a new concept, the introduction of generative AI, particularly since the launch of ChatGPT, has marked the beginning of a new technological epoch and invigorated the technology and business ecosystems to respond and move fast.
Artificial Intelligence amplifies how technology can augment human capabilities and compress operational processes, mainly through automation, but also by making human-computer interaction almost as natural as interacting with other humans.
Two Paradigms to Build and Adopt AI Solutions
As companies evaluate and design their AI strategies and roadmaps, it is crucial to consider the paradigms of augmentation and compression. By focusing on these paradigms, organizations can maximize value creation by integrating artificial Intelligence into their products, processes, and teams. Augmentation involves enhancing human capabilities with AI tools that support complex decision-making and creativity, while compression focuses on streamlining and automating processes to eliminate inefficiencies and improve customer experience.
Augmentation
Augmentation refers to the use of technology to enhance human abilities and productivity. Businesses can significantly improve decision-making, creativity, and efficiency by integrating AI systems into various workflows. For instance, AI-powered tools can analyze vast amounts of data to provide actionable insights, support complex problem-solving tasks, and enhance customer interactions through personalized experiences.
Garry Kasparov, after losing to IBM’s Deep Blue, remarked that he was perhaps the first knowledge worker to lose his job to AI. However, in his book Deep Thinking, he explores how human-machine collaboration in chess led to superior outcomes. Kasparov’s story exemplifies the concept of augmentation, where technology enhances human capabilities and drives greater results.
This concept also aligns with Steve Jobs’ analogy of computers being “bicycles for the mind.” Just as bicycles amplify physical capabilities, generative AI amplifies creative and cognitive capabilities. Jobs envisioned computers as tools that enhance human potential by making complex tasks more manageable and accessible. This vision is now vividly realized through AI technologies that simplify and democratize creative processes.
Augmentation Examples:
Compression
Compression involves streamlining and automating processes to reduce complexity and eliminate what are now unnecessary steps. AI enables this by automating repetitive tasks, optimizing workflows, and reducing the need for manual intervention. This accelerates business operations and frees human resources to focus on more strategic and value-added activities.
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By analyzing the evolution of cloud technology, we can observe the effect of compression. Moving from on-prem infrastructure to serverless platforms, multiple technology and procedural layers become invisible to end users, such as developers and IT teams. In the age of data centers, teams had to manage hardware, networking, operating systems, applications, and databases. Serverless platforms allow developers to focus only on the software and services they are building, taking full advantage of the abstraction layers that make other stack components invisible.
Simon Wardley introduced the concept of conversational programming, which evolves from serverless, incorporating the power of NLP and generative AI into the software development lifecycle. This moves up to new abstraction layers where requirements can be described in plain English and fully translated into working services or even products.
We can observe the power of compression beyond the technology stack, applying also to business processes and models. Ben Thompson’s Aggregation Theory describes how platforms compress traditional value chains by aggregating supply and demand, simplifying market interactions, and removing intermediaries. For example, traditional newspapers integrated content creation and distribution, but Google disrupted this model by aggregating and modularizing content, making it directly accessible through search. This shift transformed the distribution landscape, demonstrating the power of compression in business processes and models.
Compression Examples:
Strategic AI Adoption
A KPMG survey reveals that 77% of executives consider generative AI the most impactful emerging technology, with 71% planning to implement their first generative AI solution within the next two years.
Companies are focusing on critical areas such as enhancing customer experiences, developing new products, and improving internal operations through AI. For example, McKinsey notes that banks are using AI to streamline customer service, augment employee performance with virtual experts, and personalize marketing messages.
Successful AI adoption requires a strategic roadmap, senior leadership alignment, and substantial investment in talent and technology infrastructure. By applying the paradigms of augmentation and compression, companies can design and implement better solutions. Together, these paradigms ensure that AI adoption fits seamlessly into existing workflows and transforms them, driving significant value and competitive advantage.
References and Recommended Reading