Q&A: Nebuli CEO on putting people first in augmented intelligence

Nebuli CEO Tim El-Sheikh oversees a studio dedicated to augmented intelligence with human employees at the forefront of operations. The company, founded by El-Sheikh alongside Teacha Hamilton in 2019, looks to empower teams to deliver intuitive user experiences, using a combination of AI, science, data strategy and ethics.

This Q&A will explore El-Sheikh’s views on how to successfully deploy augmented intelligence, the skills required to see this through, and ensuring maintenance of ethical standards.

How do you bridge the AI knowledge gap before implementation?

Any implementation of augmented intelligence must first overcome misconceptions about AI – what it is, how it works, and how it relates to human employees. From Nebuli’s point of view, augmented intelligence systems differ from traditional AI offerings in three key areas.

Firstly, they help enhance and extend human decision-making and creativity instead of replacing humans with machine-led automation. Secondly, they are specifically designed and optimised to solve deeper industry-specific problems in many verticals, with a much higher level of specificity than broader, general intelligence. And thirdly, they embody the concept of explainable AI, offering unique insights and recommendations with reasoning. This approach goes far beyond the generic bird’s-eye view of business intelligence and data analytics.

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What are the most prominent challenges in the enterprise that augmented intelligence can solve?

At its core, the advantages of applying a human-centred design and partnership model are manifold and as we see it, augmented intelligence will solve two key challenges that enterprises are facing.

The first is in decision-making. Many enterprises simply lack the tech expertise to make informed decisions quickly. This is vital in the current climate, as by freeing up time spent on laborious tasks, augmented intelligence enables businesses to focus on creating value. It achieves this by simplifying the impossible process of extracting patterns and insights from big data pools. As a result, decision makers will benefit from new data strategies to smarter systems to full implementation of a new decision-making process.

Augmenting decision-making can be a game changer with few early barriers to adoption because, in most cases, it does not require replacing existing enterprise software, but enhances its capabilities using API-powered intelligence. To put this into perspective, research by Gartner estimates that by 2030, decision support and augmentation will surpass all other types of AI initiatives to account for 44% of the global AI-derived business value.

The second area of benefit is customer experience. This will be another significant source of AI-derived business value as it’s also an area where there is much room for improvement. Augmented intelligence can reduce mistakes while delivering customer convenience and personalisation at scale, democratising what was previously available to the select few. The Covid-19 pandemic has proven the critical importance of customer convenience and on-demand availability of enterprise services. Augmenting this experience will take it to new levels.

What specific skills does the workforce need in order to successfully deploy augmented intelligence?

It is essential to highlight that, mathematically and algorithmically speaking, there are minimal differences between artificial intelligence and augmented intelligence systems. Therefore, from the software engineering point of view, there are little to no changes in the skillset needed to deploy augmented intelligence in an enterprise. The key difference, however, is the application of such systems in a more human-centric approach.

Typically, software tends to be treated as the central part of any AI-driven project or overall business strategy. This model is largely ineffective, and often leads to wide-scale failures and minimal return on investment (ROI). Instead, any AI-driven strategy must put people at the centre of the strategy. We use what we call the “3 Ps” approach: People; Process; Platform. Clarifying the nature of any given challenge faced by enterprises, say Covid-19, will determine which aspects are the most important to solve. By applying the 3Ps model, executives will need to consider the following:

  • People – who is involved and how they interact
  • Processes – the systems involved and the tasks that are carried out
  • Platforms – the technology and interfaces that are used

In essence, augmented intelligence is more of a cultural change within the enterprise, rather than changing existing IT infrastructures. This means that the adoption barrier of augmented intelligence models is low. This said, adoption requires revising and redesigning existing digital and data strategies and this forms the bulk of our work with customers and partners.

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How do you ensure that ethical standards are maintained when deploying this kind of technology?

Since augmented intelligence is human-centric by nature, ethical concerns are at the heart of this model. Ethical AI is much smarter than “Lazy AI” (i.e. the AI systems deployed with minimal data privacy or data encryption requirements). Machines are not intelligent; therefore, they need to be programmed to “understand” the meaning of ethics. Indeed, this does involve significant additional work to create specialist algorithms designed around the diverse nature of people, whether they are customers or staff members, or both. But it is a critical investment for future success. Applying ethical AI strategies forces enterprises to consider a range of individual and societal harms caused by the misuse, abuse, poor design, or unintended consequences of AI systems.

This is particularly important for the new generation of customers: Generation Z. From our experience, the future of any enterprise must always start by understanding and engaging with future customers and their evolving habits and interests. We are already in the era of “Gen-Z” shoppers, entrepreneurs, users and, indeed, enterprise customers. Research by McKinsey suggests that companies must now attune to three implications of this group: consumption as access rather than possession; consumption as an expression of individual identity; and consumption as a matter of ethical concern. These form the foundations of Nebuli’s augmented intelligence model which focuses on true personalisation, user convenience, and smart, ethical technology. Understanding the evolution in customer priorities is at the core of revising existing digital and data strategies to pave the way toward successful deployment of augmented intelligence.

What plans do you have in place at Nebuli in 2021?

We’re witnessing an unprecedented acceleration of digital transformation because of the Covid-19 pandemic. Many of our customers and partners pushed forward their 2025/2026 digital plans and fully deployed them by the end of last year! Hence, in 2021, we are on a mission to help as many enterprises as possible accelerate their digital transformation strategies and stay ahead of the competition.

Unfortunately, many businesses were forced to shut their doors permanently and, from what we are seeing, the common denominator amongst these businesses is outdated digital and data strategies. In some cases, they had zero digital or data strategy.

Augmented intelligence, in our view, is the critical solution for present challenges, and we want to tell everybody about it. This quarter, we are launching a series of YouTube videos and podcasts, which will include our in-house experts and guests of thought leaders who will be discussing the post-digital transformation era. Now is the time to rethink our relationship to technology; now is the time to adopt augmented intelligence.

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Aaron Hurst

Aaron Hurst is Information Age's senior reporter, providing news and features around the hottest trends across the tech industry.