In the ever-evolving landscape of data analytics, small boutique data consultancies have emerged as nimble players, offering specialized expertise and personalized services to clients seeking more effective use of their customer data to drive long term value.
The patterns of artificial intelligence (AI) adoption exhibit both similarities and distinctions compared to previous technologies like cloud, big data, and so on. The promise of AI often sparks anticipation, triggering a widespread “me too” approach, with organizations eager to join the bandwagon. However, reality reveals that AI integration is not as straightforward as imagined.
So, as the wave of AI continues to sweep across various sectors, one cannot help but wonder: How will small, agile, and boutique data consultancies fare in the face of such transformative technological developments?
To offer an insider’s perspective for CXpose, I had the privilege of conversing with Tomas Matl, the CEO and Founder of Colours of Data, on navigating the potential challenges and opportunities awaiting these ‘specialized’ firms as AI reshapes the data analytics landscape.
In today’s business landscape, AI is a ubiquitous and crucial topic, with organizations keen on showcasing their commitment to integration. Clients are eager to explore AI’s potential benefits on process automation, enhanced customer experiences, and unlocking new business possibilities.
Tomas is clear that while he shares his client’s enthusiasm for AI’s potential, it is crucial to emphasize the need for prioritizing foundational elements.
“AI operates effectively within a mature framework of data management and automation. Overlooking foundational aspects like data collection, processing, reporting, and feedback loops hinders AI’s full potential.”
Establishing a clearly defined goal for AI implementation is essential, and the varying objectives across teams in an organization necessitate a clear vision of success.
Potential transformation for nimble players
AI has the potential to transform small consultancies in two ways. Firstly, it enhances the service proposition by integrating cutting-edge AI features, providing differentiation in the market and increasing value to clients.
“AI allows us to fine-tune services and show clients the art of the possible; e.g. image processing to ensure the interior of the car being built on the assembly line contains the correct combination of 300+ elements that could be used for accessory levels and bespoke car configurations. Equally, we can leverage GenAI to provide application users with easy-to-understand error messages that are created by AI from machine-generated error prompts,” Tomas explained.
Secondly, AI serves as a powerful tool, simplifying the way teams work, saving time used in the past to do for example, research, or repetitive, or semi-manual tasks, and acting as a valuable ally in the way projects are delivered.
How will small, agile, and boutique data consultancies fare in the face of such transformative technological developments?
Tomas shared about another data project. “We were engaged in a Telco project, where the client required building the model for NBO (Next Best Offer); this required data transformation to standardize the description of products in our clients’ vast product portfolio. Giving the AI a prompt – an example of the transformation done for a selected product; it generated the transformations for the rest of the portfolio in just a few moments. This not only saves time but also reduces manual effort, enabling our team to focus on strategic tasks, fostering innovation, productivity and creativity.”
Staying at the forefront of the field involves understanding the capabilities of new tools, comprehending their impact on our work processes, recognizing the value they bring to our clients, and refining our creative approaches to align with the possibilities AI opens up. Tomas found a way to leverage this and shared, “To future proof our team and ensure adequate resourcing of our projects, we prioritize a culture of continuous learning.”
In another use case, when AI handles the coding of business logic, it liberates developers to redirect their efforts towards crafting intricate user interfaces. “This allows for a more intensive and innovative collaboration with clients, fine-tuning the visual aspects to perfection.”
AI in small consultancies: Best practices to note
At Colours of Data, the team recognizes the importance of staying informed through extensive reading and listening, delving into industry trends, and learning from the practices of leaders in the field.
Tomas pointed out, “We actively seek inspiration from various industries, combining best practices to tailor our approach uniquely. Regular communication with our technology partners ensures that we collectively evolve our propositions to stay ahead of the curve. We also watch our competition and fellows in the industry very carefully. The exchange of wins and challenges experienced by all is a great way to generate new ideas, avoid errors, and dead ends.”
But what about the risks of AI reducing the need for consultancy service? The phenomenon of machines and technology gradually replacing human tasks is not new; it has occurred throughout history.
To this, Tomas opined, “Instead of viewing the advent of AI as a threat, we see it as an opportunity to leverage our uniquely human capabilities in strategic and creative thinking. By actively engaging with the evolving landscape of technology, we can guide its integration to the benefit of our clients. We are grateful to be able to deploy AI for tedious and manual work and focus on things AI will not be able to do, for example. working on adoption of the new approaches, technologies and tools in our clients’ teams as this is critical for the success of our projects. Or creating the best fitting and the most innovative architectures that address the problems clients give us to solve.”
What remains crucial is harnessing human intelligence and creativity to envision how these emerging possibilities can enhance our lives and contribute to the success of our companies.
Summary:
Small consultancies hold significant opportunities in successfully integrating AI, not only into their own operations, but also as part of their service offerings. Before they do, however, It is essential to have foundational elements in place and that clients have clear alignment of their objectives across verticals when it comes to the benefits of “embedding” AI.