The Organizational Impact of a Foundational GenAI Strategy
Copyright by Stephan Klaschka 2010-2025
Innovative Sputtering
AI is hyping and Generative AI (GenAI), in particular. It emerged and rose in a short time to offer great opportunities and rewards for practically everyone. Nonetheless, companies struggle to fully embrace and deploy AI strategically and effectively.
Limited GenAI experiments mushroom in various departments but, soon enough, they don’t achieve their full and meaningful potential, and run out of steam, favor, support, and funding. Why is that?
We understand AI, at this stage, to become an augmentation to the workforce, a digital partner to empower and propel employee productivity. Each department seeks AI-worthy applications, low-hanging fruit, for implementing GenAI-based solutions. Many companies jump head-first into the water in this fashion so as not to miss out on a timely competitive advantage. Very few seem to approach AI more level-headed with a sound and comprehensive AI strategy.
Starting at the Wrong End
I offer this explanation: The trouble starts by thinking too small, too isolated, too siloed. The common approach is to integrate AI technology into the existing organizational structures - its divisions, functions, and departments- that are working side-by-side and often enough in silos with little incentive to collaborate closely to achieve the overall mission (see also Why mature organizations can’t innovate and Overcoming the Three Big Hurdles to Innovation in Large Organizations).
After all, that’s what company departments were originally established for. This also extends to the composition of employee incentives and career paths designed to match and progress through the structure of the organization. This design is to meet the departmental and functional goals of the organization. The separated departments, people, systems, and data form silos with the common success metrics focused on within the siloed structures. They offer no paramount incentive for comprehensive and focused collaboration.
Consequently, in today’s organizational structures, hardly any roles exist that are incentivized to deploy AI to its full potential cross-functionally and to open up safe spaces to experiment broadly. Companies tend to remain internally focused with metrics that apply within their wall and employee incentives aligned with this closed-wall perspective.
And so, one organization after the next misses to support and align with the outcomes that matter most for the customer: the value generated along the customer’s journey.
Taking the Path of the Customer Journey
Aligning with the true customer journey to generate value that is important to the customer is key, and data forms the core of the AI-based transformation. The actual customer journey and its outcome are, likely, very different from the often proudly acclaimed ‘customer-centric’ accolades in glossy presentations and pitch decks. It requires stepping back and taking an honest and detailed new view entirely from the customer’s perspective.
It needs to connect the dots of people, data, and processes to measure the value created for the customer at each step along the way. This becomes the blueprint for the data-centric organization in which Gen AI together with other systems and tools become levers that enable the staff to create the value the customer seeks and is willing to pay for. Creating this value for the customer is easier said than done, so how do we get there?
Saddling the Horse
Truly leveraging the data of an enterprise requires bigger and more cross-functional thinking. The challenge is to enable all parts of the organization to achieve the intended objectives and with data-sharing at its core. It may require more than even a unified data model: This most comprehensive approach then lends itself to adjusting the organization structure in support of the new mission.
Sharing the relevant data effectively will likely require restructuring and reorganizing around the new mission to unlock the value creation with the realignment of organizational structures, processes, and incentive schemes.
A new mindset is needed through the organization to achieve all this is supply chain thinking around value disciplines to build the new ‘product’, i.e. the value creation truly for the customer with methods being applied across the organization to map and elevate the customer journey in new ways: from identifying the value drivers, effectively sharing the relevant data, remodeling the organizational structure, aligning the incentive system, and so on.
Yes, this approach is a major, transformational overhaul that, by its very nature, bears its risks. It includes re-inventing the business model, so it may not be for the faint-hearted. Instead of experimenting with proof-of-concept in one or a few departments, the approach entails a company-wide proof-of-value in the operational model along the customer journey. The metrics strictly follow the value generators to guide the way and reshape, where necessary, the very structure of the organization.
While the necessary effort is high, the outcomes are likely the largest differentiators to any competitor and make a real difference for the customer, which the customer is willing to pay for.
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