Meta, the multinational tech conglomerate behind Facebook, recently shared details of a deliberative democratic process focused on informing decisions around its so-called metaverse. Experts are calling the tech behemoth’s efforts a giant experiment in governance. Moreover, it’s an experiment heavily rooted in artificial intelligence.
With Meta’s democratic process-focused pilot now complete, the company’s ongoing efforts are raising new questions about product value creation. That’s especially true concerning revenue-led merger integrations, including those within the private and government sectors.
It’s an area of particular interest for Bane Hunter, a global executive and product specialization expert known for creating value in the tech sector. Yet, according to Hunter, and with product value and revenue firmly in mind, there’s still a significant need for improvement in deliberative democratic processes at government and other levels. Nowhere is this more apparent than in applying these and similar processes to AI.
How are brands like Meta using AI-led governance to increase revenue?
Meta isn’t alone in using AI-led, governance-focused initiatives in its business. It follows widespread interest in so-called democratic innovation, particularly when utilizing one or more AI systems. Other brands leveraging the same processes include DeepMind, Google, and, of course, OpenAI.
It’s hoped that what’s increasingly being called deliberative democracy will benefit businesses across the board. That’s as Meta’s recent and undeniably valuable proof of concept looks set to shape the surrounding landscape. With that, product values will likely increase exponentially, including across merger integrations in the government.
How does the underlying process work, particularly around governance?
In Meta’s case, the company best known for running Facebook enlisted over 6,000 individuals to discuss company decision-making processes in the present and future. Whether focused on merger integrations, bolstered product values, or increased overall revenue, the multinational tech conglomerate’s efforts were deeply rooted in governance.
It’s a process that’s likely to become more and more AI-led, especially in the next 12 months to two years. It’s imperative to remember that where AI underpins any process, governance is of the utmost importance.
In Meta’s case, the company partnered with Stanford University on its efforts, which then ran proceedings. Such measures mustn’t be overlooked, especially where one or more merger integrations are on the table. The same applies where similar processes will take place using generative and other forms of AI.
How can businesses create product value across merger integrations?
Whether in the government or elsewhere, creating long term value is essential in increasing revenue/positive outcomes – that goes without saying. However by combining merger integrations/efficiencies of reducing duplicative efforts, enabling deliberative democratic processes, and artificial intelligence, the rate at which value is created increases exponentially.
With that, businesses looking to follow in Meta, DeepMind, Google, or OpenAI’s footsteps must learn how to adapt based on verifiable, appropriate and accurate data only. There’s also much to learn from the associated transformation and effective program management practices that have, almost in parallel, gained similar traction in recent years.
However, for such processes to be both democratic and successful in generating increased revenue or simply market share, other considerations are vital. Chief among these considerations must be accountability and understanding of business outcomes at all levels, from first line product managers to C suite stakeholders, especially when transparency is crucial for a successful ideation, launch and ongoing support/evolution of a given product.
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