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What is Generative AI, and why does it matter?

The term "Generative AI" (GenAI) refers to AI systems capable of generating various forms of media such as text, images, and more. Recently, advancements in GenAI systems have reached a level rivalling human performance. This development enables large-scale, AI-driven value creation and facilitates the adoption of these technologies by end-users, a feat once thought to be unachievable.

Although GenAI is not a magic wand that will replace human effort, it does constitute a paradigm shift in the large-scale automation of work, life & society.

An accessibility revolution enabling last-mile delivery of AI capabilities

Non-technical users can use GenAI tools and interact with AI solutions in unprecedented ways. For example, the GPT store by OpenAI lets non-technical users program with natural language, state-of-the-art AI-powered assistants and applications that will soon be sold in OpenAI's very own GPT "App store".

Despite the ease with which non-engineers can build their own GenAI prototypes, there is no drop-in replacement for developing a well-designed product. GenAI is a shortcut from an empty page to a draft, from idea to prototype.

Industrial applications that meet the quality expectations of customers and operations teams and mitigate and manage the risks that automation can bring still require concerted effort, including holistic expertise in AI systems, data and cloud platform design and a dose of strategy and business understanding.

For example, it's easy to build a question-answering (QA) GenAI system that answers questions in natural language on top of your company documentation. It's easy to build a prototype on a small amount of data or for a single question. But, most people want to use these QA systems as flexibly as they converse with humans or want to scale up a small set of documents in the prototype phase to thousands and even millions of data points. A QA GenAI prototype can take minutes - and, in isolated cases, be valuable when the data and scope are minimal. A fully functional QA system that can answer many different types of questions and use an extensive data set while still providing answers that save time for the end-user can take weeks, months, or years, depending on the definitions of success.

Another example in the creative space is image generation. These days, the GenAI-powered generation of visuals is becoming commonplace. Yet, for any use case that requires fine-grained editorial control, typically those cases where images are used in professional settings, the existing out-of-the-box solutions that promise value in minutes fail. For instance, imagine you want to generate a picture with a particular composition, structure, or text box. With today's tools, you can approach one of these on its own, but combining all three is typically infeasible. In practice, human experts still use traditional image editing tools in conjunction with the power of GenAI.

GenAI synergises human and machine intelligence to get the best of both

Most processes have been digitalised in the last two decades as software has entered the knowledge and creative work world. Now, because GenAI rivals and even surpasses human performance in many tasks previously thought unsolvable by machine intelligence, GenAI will start to eat anything digital: All digital processes in companies are potential targets for automation or augmentation.

Consider Github Copilot, an AI coding assistant that allows developers to spend more time on the value-creating components of their job - whether it is designing systems that fit the context of an organisation or delivering projects faster. Within the next few years, any conceivable task in the digital domain will get its copilot to assist people in working more effectively.

Yet, GenAI is not a replacement for humans, neither in the development of the systems nor in the processes and tasks whose efficiency it aims to improve. GenAI boosts human productivity and creativity but ultimately cannot replace humans wholesale. Human ingenuity will remain a vital component of any value chain.

What can GenAI do for enterprises? What are typical applications?

GenAI can promote productivity across a wide range of company functions.

Marketing & sales: Crafting unique, personalised content to engage audiences and maximise ROI.
Technology & Engineering: Assisting with coding, documentation, and reviews. Faster prototyping to build a support base with stakeholders.
Risk & Legal: Handling complex inquiries and managing extensive documentation.
Customer support: Human-like chatbots that improve customer experience and reduce the load on customer support.
Cross-functional Applications: Creating more efficient internal search engines for company data, enabling quicker access to information.
Human Resources: Automating initial resume screening, scheduling interviews, and providing insights for employee engagement and retention strategies.
Finance & Accounting: Automating routine tasks such as data entry, generating financial reports, and providing essential financial analysis.
Supply Chain & Logistics: Enhancing demand forecasting, route optimisation, and inventory management through genAI-infused predictive analytics.
Research & Development: Assisting in analysing research data, literature review, and hypothesis generation.
Product Management: Supporting market research analysis and gathering customer feedback for product improvement.
Corporate Strategy & Business Development: Providing market trend analysis and competitive landscape insights.
Training & Education: Creating customised learning modules and providing automated assessment tools.
Healthcare & Life Sciences: I assist in medical research by analysing data and supporting diagnostic processes with preliminary analysis.
Environmental Management: Analysing environmental data for sustainability reporting and helping manage regulatory compliance.
Retail & E-commerce: Using predictive models for inventory management, customer preference analysis, and personalised shopping experiences.

Building prototypes with GenAI is easy; scaling them for adoption is where most competitors stumble. We prefer to focus on creating lasting value with AI and data systems, propelling your business by leveraging short and long-term GenAI benefits.

Deriving sustained value from Generative AI: supporting your journey

Two significant challenges exist in extracting value from GenAI. We're uniquely positioned to help you tackle them.

Robustness: Scaling GenAI solutions is a complex task. It's one thing to create a prototype; it's another to develop a solution that can handle millions of requests reliably—many falter here, needing help to ensure consistent, high-quality performance under varying loads and scenarios. We can help your GenAI solutions scale alongside your business needs.
Compliance: GenAI interacts extensively with users, data, and systems, opening up risks in cybersecurity, privacy, and brand reputation. Compliance becomes even more critical in sectors like finance and healthcare, where the stakes are high and regulations stringent. We have the expertise to advise and execute compliant Gen AI solutions.

We help you derive value from GenAI

We have already implemented GenAI solutions and actively translate continuous GenAI evolutions in academia and industry to their strategic implications. We are committed to nurturing long-term customer relationships, focusing on delivering value to you beyond just offering staffing and services - we will tell you where GenAI is valuable and feasible and where it isn't.

Finally, and most importantly, we understand the challenges and opportunities in Generative AI and have the capabilities required to address them cohesively with our three key teams to enable vertical integration of GenAI into the fabric of your organisation:

AI & Analytics: We don't just implement GenAI; we ensure it adds real value. Our team can identify opportunities as well as develop robust GenAI applications. The AI and analytics team manages the entire lifecycle, balancing innovation and pragmaticism. LLMOps, MLOps, RAG, RLHF, whatever it is, we can help you make it work and align it with strategic objectives. Moreover, we can tell you where GenAI makes sense and make it work at scale.
Data & Cloud: Our expertise lies in creating a solid foundation for GenAI applications. The importance of a scalable, secure data and cloud infrastructure cannot be overstated for most enterprise applications of GenAI - without it, sustained value cannot be unlocked. Our team are world experts, recognised by partners such as Microsoft, dbt, and DuckDB, as key experts in the modern data stack. After all, without data, there is no understanding of in-house company context and processes, and you wouldn't expect a human to do well, either. GenAI is no different in that regard: You will need quality data.
AI & Data Strategy: More than being lean is needed, and a strategy informed by the ongoing GenAI revolution is critical to stay relevant and capture more market share. We help you navigate an unstable terrain, turning technical disruptions into strategic business opportunities. We can help you iteratively launch a GenAI strategy aligned with your strategic objectives.

Reach out

Jump on a call to find out more. Feel free to reach out to us.

Want to read more on GenAI, have a look at this lightweight guide to GenAI.

Supporting Your Generative AI Roadmap