This is the second article of a 2 part series on Benevolent Mavericks. To read the first article, please see: Why organisations hoping to transform need a ‘Benevolent Maverick’.

As organisations rapidly deploy generative AI (GenAI), one of the biggest challenges they will face is how to get a return on investment. There will be plenty of use cases, in fact, a laundry list of possibilities that will get collected across organisations as people get excited on how to embed AI in current processes, products and services.

However, similar to the ‘death by dashboards’ in the data visualisation and insights era, organisations will soon find themselves in a scenario where investments in resources, data transformation, time and money result in incremental, if any, changes in customer experience, productivity and growth.

Hence, organisations serious about creating new value pools from AI innovation and technology, need people that possess the common traits of a ‘Benevolent Maverick’, which include: strategic and innovative thinking; skills in leadership, communication and stakeholder engagement and experience in E2E product management from strategy through to execution, preferably with domain knowledge of data and analytics.

This is not to say that organisations need to hunt for ‘unicorns’ and find all these traits in one individual. An AI Dream Team will be comprised of a team of with varying traits of a Benevolent Maverick to cover the strategic innovation AI product lifecycle alongside the technical cross-skilled teams that will building the data and design architecture and products.

Why Benevolent Mavericks?

Over the years of data and technology innovation, there has always been a rift between the perspectives, communication styles and ways of working between business and technical teams. In what may now seem like a fairly dated 2018 article, McKinsey was forward-thinking in their recommendation for organisations to develop and find “Analytical Translators” (ref).

These individuals were deemed critical for ensuring that “organisations achieved real impact from their analytics initiatives”, something even more relevant today given the greater financial and non-financial investments required to back up AI projects. Translators were the bridge between technical teams and business operations.

Importantly, ‘analytical translators’ are not data architects, data engineers and do not possess deep technical expertise in programming or modelling.

There are two misconceptions around the skills of people involved in co-delivering great data and AI products with technical teams. The first is that people with domain expertise in data and analytics need to be engineers or computer scientists. Many other fields use data including finance and accountants, economists, statisticians and epidemiologists, to name a few that can add value and work with computer scientists and engineers to get the great outcomes.

In fact, teams that are cross-disciplinary and have people with cognitive diversity perform better.

The second misconception is that people working on delivering AI products have to be on the tools and coding or building software. There are other important roles in an AI product team that do not require these technical skills including strategic thinking, innovation, program management, ethics and regulatory expertise, and design to name a few.

In this article, I will go a step further and argue that given the diversity of use cases and the stakes at play, analytical translators are not enough for organisations to reap the greatest value and ROI from GenAI opportunities.
Organisations need people that are Benevolent Mavericks, who can act as the translator along the product lifecycle but that can also think differently, challenge the status quo and help see non-obvious use cases.
Without these individuals, organisations will be at risk at investing only in the obvious, traditional and lowest hanging fruit use cases which will deliver low returns and incremental value.
Benevolent Mavericks bring a different perspective and solution to problems and become obsessively passionate about their cause, rallying troops and pushing through the complexity and internal organisational barriers to get vision up the windy hill of setbacks to realisation’s peak.

**‘Benevolent Mavericks’ in the AI product lifecycle**

In the diagram below, is a visual of the 4 key responsibilities of ‘Benevolent Mavericks’ in a GenAI product lifecycle:

Strategy and Innovation

2. Stakeholder and Partnership Engagement

3. GenAI Portfolio Manager

4. Connector and Communicator

Strategy and Innovation

Benevolent Mavericks are the people in an organisation who bring a fresh outsider perspective, who are innovative and creative thinkers and who add value by identifying alternative ways of doing things that are often unorthodox and non-traditional. The visionary Benevolent Maverick can be at any level in an organisation.

Organisation’s with a culture that support and encourage people to be adequately informed and have channels to communicate up ideas and solutions are more likely to identify original and pioneering ideas, or even non-revolutionary ideas that solve real ‘thorny’ and important problems.

In the diagram below: the ‘Before’ on the left side of the image depicts the traditional and obvious way to sell Lemonade which has barriers to customers because the location is fixed.

The reimagined business model in the ‘After’ panel on the right side of the image uses a business model that is customer-centric and provides the product to consumers using a faster, flexible and more personalised approach that expands the consumer market and potentially opens up possibilities for partnerships and delivery optimisation to provide a competitive advantage over traditional lemonade shops.

The ‘After’ business model is no longer unique or even disruptive; global consumers are accustomed to using Uber, DoorDash, Menulog and other similar companies. However, what this image depicts is how transformative and revolutionary the right, customer-centric business model design was in its time compared to the former accepted way of structuring and delivering products and services.

The opportunities to drive growth using GenAI can be categorised into three broad approaches:

Approach 1. Incremental improvements on existing processes through automation and predictive modelling. These are pointed and often tactical solutions with minimal changes in current designs, but can provide smarter and faster ways of doing things.

Approach 2. Larger value creation and profitability through product or service innovation. These are less around pointing a hammer at nails and thinking of where AI tools can be used and more about conceptualising solutions to customer problems and including types of AI into the design of solutions where it makes sense and adds real value. This initiatives still require serious inquiry; research from the perspective of customer needs and pain points, the business, and the broader market and competitive landscape.

Approach 3. Opportunities for significant value creation from long-term strategic thinking that involves reinvention, finding untapped value, extending beyond core business, and expanding the ecosystem.

Benevolent Mavericks are helpful in ideating and prioritising use cases and ensuring there is sufficient ‘stage time’ for proposing the latter two approaches, which require more complex and transformational investment to reap the rewards of growth and revenue.

Stakeholder and Partnership Engagement

The role of the ‘Benevolent Maverick’ is to embed AI technologies across all lines of businesses to solve problems. While this persona needs to be technically savvy, the challenges for this role are largely barriers relevant to organisational cohesion, such as breaking down silos, removing blockers, prioritising which problems to solve and directing resources to enable the success of AI solutions.

Benevolent Mavericks act to harmonise the workings and communications between business executives, data professionals and IT delivery teams to ensure that the right opportunities are pursued and realised to reach their promise.

Integration of these team members into AI delivery teams ensures organisations move AI beyond the IT department to develop strong linkages between business operational teams and IT delivery teams. One of the mission critical aspects of developing these various partnerships is trust and a shared vision.

GenAI Program Manager

The amazing and also at times frustrating trait in individuals who passionately believe in a better way of doing things is their persistence. It is exactly this trait when combined with benevolence that inspires others to follow them and seek purpose from achieving a common goal.

As organisations gradually embed advanced analytics and AI use cases across their enterprise, a PMO-type of AI transformation office can be helpful in tracking these initiatives, and developing standard processes, tools and governance to create efficiency and transparency and importantly, to connect the dots and develop a system for sharing resources, allocating funds, learning from common challenges and tracking negative and positive events and outcomes.

Connector and Communicator

The Benevolent Maverick is a leader who not only who draws people to the cause but allows their input and creativity to shape the movement.

Benevolent Mavericks possess a growth mindset that is somewhat infectious; there are energetic and passionate individuals who are driven by wanting to create something new rather than maintain or extend the current way of doing things.

These individuals display a strong moral compass and show a genuine desire to do what is right for the organisation. For innovative AI projects to succeed, enterprises need these leaders to inspire others using their strong sense of purpose and unconventional spirit to drive outcomes.

Another critical role for Benevolent Mavericks, is to embody a ‘human API”, meaning they are effective at partnering with business subject matter experts and technical specialists. In a sense, they are like multi-lingual tributaries across the organisation.

They are effective communicators and translators between technical specialists, business leaders, executives, sponsors, marketing, and customer channels. They add immense value to ensuring AI projects solve the right problems, have elegant designs, get the right specs built according to the requirements, get then delivered, implemented and adopted effectively.

Summary

AI is a transformational technology that will disrupt and reshape how we operate on an individual and organisational level. Harnessing value from AI is a competitive game; figuring out how to successfully achieve growth is not obvious or easy.

Organisations that attract technical talent and are able to diversify their workforce in gender, racial and cognitive thinkers will have a competitive advantage. This means integrating a pool of new hires from the outside that have not been in the business or even the same industry doing the same years for years and years.

In many ways, this means recalibrating the HR department from a tick the box exercise, re-educating hiring managers to look for hires that are dissimilar to themselves and to ensure hiring processes that only pay lip service to transferrable skills, like problem-solving, analytical thinking, curiosity, resiliency, and creativity, develop objective ways of scoring these critical attributes to give them sufficient weight.

Thanks for reading!

‘Benevolent Mavericks’ help create AI-fuelled organisations.