In the overarching story of technological progress, we are moving from the “Age of Information” into the “Age of Intelligence.” Swift developments in Generative Intelligence (GI) are poised to transform society, revolutionize various industries, and alter the nature of work. This shift challenges our conventional perceptions of economic dynamics and their connection to human productivity and societal well-being.
In today’s world, merely showing up is insufficient. The repercussions for those who lag behind — whether as individuals, industries, or institutions — can be severe Each transition represents an evolution in life on Earth, with technology consistently playing a pivotal role. The initial transition was marked by the discovery of fire, followed by advancements in transportation, communication, internet, and now digital. It’s important to recognize that each of these transitions has profoundly shifted life on our planet to a better place. Always changing the Structures (Relationships), Synergies (Culture) and Systems (Organizing and Orchestrating Work). In the past, these shifts have been slow and not guided by design. The current shift needs human intervention and intent to guide the advancement of technology; both to erase the deficit of contributing to the Quality of Life and to the need for assuring a more sustainable future.
The concept of intelligence can be defined as perception, which is the ability to inference meaning. In today’s internet-driven world, characterized by divisive narratives with unprecedented distribution and reach compared to previous generations, it’s essential to recognize how life can be positively disrupted. This transformation occurs when new Data, Talent, Materials/Resources/Energy, and Investment are fused to create Products and Services powered by Value, Intellectual, and Human Capital. An Intelligent Infrastructure, powered by Artificial Intelligence (AI) and Generative Intelligence (GI), plays a crucial role here. The challenge of the Intelligence era lies in our ability to design how this fusion operates within a context.
This is a video link to a TEDx talk by Malcolm Gladwell (https://bit.ly/Revengeofthhetippingpoint), who returned to New York after 25 years to explore the hypothesis from his first novel. He delivers a crucial message in this video. Previously, he thought that projecting confidence in one’s writing was how leaders should behave. However, he now realizes he was mistaken; it is perfectly acceptable to be vulnerable and uncertain. He emphasizes the value of engaging in a process of Learning, Training, Experimenting, Performing, and Measuring to validate one’s positions. This message is particularly relevant in today’s world, which is fraught with the prospect of no one being an expert and the demand is for not Searching for solutions to the numerous challenges our societies face. It is about contextualizing it to an individual and aggregating it to a societal level with data evidence.
The pressing question we face is whether humanity is prepared to take responsibility for shaping the age of intelligence, or if it will allow technology to take control.
Yuval Noah Harari’s Best Selling book Nexus explores the role of information networks in shaping human history and the impact of AI on the future. Harari urges us to think critically about the future we want to create. These Information Networks we have come to know as Communities can now be digitized to a Glocality. And it goes without saying that they have to be contextual for each person to participate immersively with intent to create the right impact that can all trust.
Fareed Zakaria, in his recent bestselling book “Age of Revolutions,” highlights that invention and innovation are the fundamental drivers of modern history. He contends that the Dutch Revolution significantly boosted per capita income in Western societies supported by the data produced by Angus Maddison, distinguished British economist specialising in quantitative macro economic history. Today, despite advancements, leaders are tapping into a cultural discontent, almost encouraging people to revert to the past. This phenomenon is observable globally, whether in the U.S., India, China, or Germany. Such a mindset stands in opposition to growth. To envision a future that differs drastically from anything we have known or experienced, we must address human shortcomings in overcoming challenges. This transformation can only occur with a design learning mindset, one that focuses on potential rather than just performance.
Transformation or change doesn’t happen simply by a group of individuals contemplating it. Instead, it requires a three-step approach: simplifying legacy processes, modernizing systems, and disrupting ecosystems.
There is no doubt that intelligence is personal, and all processes, systems, and ecosystems are an aggregation of individual actions. Thus, it is reasonable to shift our focus from enterprise to individual if we aspire to lead an intelligent life. Each individual plays various roles across the seven stations of life: Environment, Education, Health, Wealth, Mobility, Technology, and Governance. It is essential to understand the relationship between the data generated in a process as both human and machine roles transition from creation to consumption in a continuum. This understanding is achievable by establishing the structure (graphical nodes and their interconnections) that guide the process alongside synergies (values, convictions, and assumptions) that dictate access, authentication, authorization, permissions, and privileges. Additionally, systems must be open for collaborative sharing on a glocal (globally local) level within a trusted ecosystem.
Five factors pose a major problem to the shift of the age of information to one of intelligence:
Enterprise Applications Modernization ($60.87B by 2032):
Source Mertech Data
Corporations are focused on Modernizing their Strategic and Technology debt ridden systems worldwide with a staggering $60.78B spend that is in no way contributing their positioning for the future. This is merely what keeps their businesses afloat. It is necessary but not the only strategy to adopt and when you see it against the evidence of how they fare, it makes it worse:
74% of companies fail to complete their app modernization initiatives.
92% of enterprises are working on modernization projects with projects often taking up to 16 months and costing around $1.5 million.
Innovation Management ($1.62T by 2025):
Source Bloomberg Intelligence
Most corporations in the world neither have a stage gated process from Conceptualization to Commercialization in a continuum nor are they supported by Technology Systems that permeates the environments of Solution and Application seamlessly. It is therefore not surprising that:
95% of innovation initiatives fail.
Average time from idea to implementation: 18–24 months
Talent Management ($25.94 billion by 2030):
Source: Fortune Business Insights
The emerging trend in Talent Management involves the creation of Global Capability Centers (GCC) specifically designed to attract top talent worldwide to support corporate business goals. Interestingly, the startups that stand to gain the most from this approach have yet to fully adopt this strategic option. Both incumbents and new entrants are still struggling to simplify, modernize, or disrupt their respective sectors due to challenges associated with modernizing enterprise applications. In contrast, the GCC strategy could introduce innovative concepts with clarity on fusing Work, Workforces, and Workplaces. The ongoing focus on Performance instead of Potential is detrimental, as illustrated by the following statistical points:
82% of companies can’t assess employee potential accurate.
71% of L&D programs fail to deliver business outcomes.
Digital Transformation ($3,290B by 2030):
Source: Markets & Markets Research Report; Taylor & Francis Research Report
One of the significant issues seen in corporations globally is their failure to grasp the importance of Digital Transformation, often viewing it merely as another technological update. They have created silos for separate leaders in digital, technology, information, innovation, and products/services, each safeguarding their own interests and competing for budgets and recognition at the CXO level. In reality, these structures must evolve and collaborate for the betterment of the entire organization. Is it any wonder then that:
1. 70% of initiatives fail to reach stated goals.
2. $2.3T is wasted on failed digital transformations currently.
Design Thinking (USD 14.9 billion by 2032 at CAGR 7.25%)
Source: Business Research Insights; Training Industry Report 2023
Design Thinking is still primarily an offline process and has not been updated to align with modern technological capabilities and opportunities. It should integrate with organizational Learning Programs, enabling most of the workforce to actively contribute to Solutions and Applications. The first challenge lies in its application for Problem Solving, while the second is its perception as a standalone activity. Annually, over $300 billion is spent on corporate Learning and Development, yet the effectiveness rate remains at just 25%. There is a pressing need to transition from Design Thinking to Design Learning, creating an environment that fosters Learning, Training, Experimentation, Performance, and Measurement as an ongoing process. However, insufficient attention is given to Visualizing and Implementing this change.
Setting Versus Following Trends
In these times, it’s crucial to set trends rather than merely follow them. As you recognize that your systems will be influenced by a Systems of Agents, it’s essential to design your business model for personalization inverting the conventional industrialization. Model the data visually to connect roles and enable real-time computing capturing data from Creation to Consumption in a Continuum, allowing agents to serve every role contextually within the ecosystem through their roles managed by a Digital Identity. This is a vital step in modernizing your systems. Avoid jumping into disruption, as neither your organization nor your customer base is prepared for it. You need to cultivate a process of Education, Ownership, and Commitment to ensure that Customers and Consumers not only get on board but also truly enjoy the Engagement (UX) and Experience (UI) provided by Intelligent Agents (UXL). Only then can you begin the transition from an information-centered era to an intelligent one. Ultimately, the key is how enterprises can refocus their Product/Service Life Cycle to emphasize the Customer/Consumer Life Cycle.
AI / GI Opportunity
As illustrated in the graph above, there is a significant opportunity to integrate Artificial Intelligence (AI) and Generative Intelligence (GI) into your strategic business applications. However, without a clear focus on fusing Data, Talent, Materials/Resources/Energy, Investments (at the intersection of Value, Intellectual, and Human Capital) and Intelligent Infrastructure, you risk wasting your time, energy, effort and money. Demonstrating strong leadership through the five dimensions of Aspiration, Agility, Anticipation, Authenticity, and Ability is essential in prioritizing design for Potential before Performance.
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