The Artificial Intelligence Blueprint : Understanding the overarching priorities of regions, industries and value chains

Those who work with AI realize this very quickly. This feature magnifies intelligence and diligence. The fact that a single snippet of AI could be incorporated in similar systems across the globe, makes it a feature to be handled with great attention. Hence, the need to reconsider the overarching approach to AI.

Humans are relentless about improvement and innovation, in creating and seeking the new and the better.?Post the full adoption of industrialization and the saturation of the IT economy, the world almost seemed to have reached a point of beating the response times by a few milliseconds.?'The planes can only go so much faster' kind of a plateau.

ENTER, a feature , partly theoretical, partly science fiction, and now a programmer's ally as well as arsenal; ARTIFICIAL INTELLIGENCE. ?

Three things happened that made AI possible.?

• A lot of devices (billions) that produce and consume data?
• Access to internet?
• Users (billions) and Usage?ie. Activity on the internet??

AI is now at the heart of the new wave of value creation. My sting in the AI industry has introduced me to newer operational realities and possibilities. In terms of scale, the variety of applications and the reusability of the chunks of code, AI is an potent capability in the hands of programmers, the appliers and the deployers.?

Allow me to reiterate the most underrated fact before we proceed further; AI is the most context dependent feature that is there in the world of applications. Think AI, think context - value. ??

To effect?multi-level?interventions, to transform entire industries, to command the operations over a domain, to sustain operations in volatile conditions, to leverage 'change' itself, the AI blueprint is the singular area which could drastically alter the future prospects of regional, economic and industrial interests.

Knowing how to leverage AI for Value Creation, Command and Coordination:

AI as a feature is a dream come true of tinkerers. For these minds, AI is about finding the shortest or the wittiest way to solve a problem.?But there is a lot of difference between using AI as a feature and leveraging AI. No wonder the brightest of minds in the industry and academia are pondering over the implications of this constantly evolving capability.

In the right hands, with a right map, AI can be used to

1. Create Value continuously
2. Command Operations effectively
3. Meet emerging requirements and new varieties of operational and functional requirements
4. Simplify and accelerate high volume workloads

Environmental Awareness, Situational?Awareness, Moment to Moment Intelligence :??

In one way, AI lets you listen and sense the environment, with a frequency and accuracy that makes the unnoticeable stand out. A sort of a “minute-to-minute" awareness of the situation.?

In another way, AI helps one automate workflows, which earlier would have needed human intervention to match an input with its priority.??

This combination of scale, flexibility and inclusiveness makes it a thriving programmable sensory system that can guide machines, teams, operations and processes based on pre-set lines of action.

Factoring in Regional Sensibilities and Nuances :

A Europe centric AI CoE would have an entirely different gamut of offerings and capabilities when compared to an AI CoE for say APJC. While the principles and lifecycles remain the same, the purposes, templates and the frameworks would have varying degrees of differences not to forget the statutory compliances that tend to vary periodically as well as regionally.

The deployment of AI features have implications that transcend the economic, industrial and national ecosystems. Because AI brings with it the potential to effect panoramic multi layered capabilities across the ecosystem, factoring the priorities of the region is a task for the strategists and the industry leaders.

Take Europe for example:

1. The unique geopolitical nature of Europe
2. The aspirations of the people of the European Countries
3. The common interests and commitments
4. The areas and functions that overlap
5. The outlook of the economic activity

Or take Asia for that matter.

1. The overall industrial potential of the region
2. The emerging developments in technology adoption and policy imperatives
3. The availability of human capital
4. The commitments to global causes
5. The potential for collaboration with Europe and other regions

Now, could there be a realm for opportunities to exist in a digital corridor between Europe and Asia ?

1. How could the AI capabilities reduce the processing gaps across operations in the two regions with unique dynamics
2. How could the elements of language, search and priority be incorporated into AI engines to enable faster knowledge transfer and executions.

The same goes for Nation States with multiple States and a federal structure:

1. To enable richer coordination through precise, real time inputs for incidents like hurricanes and floods which do not operate within the parameters of state jurisdictions.
2. To make it easier for the state stakeholders to contain pandemics, catch offenders or to track fleets
3. To harmonize power grids and water supply across the states

AI's bootstrapper friendly nature makes it ideal to produce outlier solutions :??

Unlike earlier where dedicated investments were required to develop and operate high impact software, AI especially its proximity with?open source?languages?and?an unbelievably high flexibility in arriving at solutions, makes it not only an approach but also a level playing field. All it takes is a cloud services subscription, a cyber security awareness and deployable AI software to go to market with solutions.??

So, it makes sense to keep the options and the APIs open for the coders who want to make something on the open API to solve their local problems with their coding skills.

In fact, with an increasing programming capability and open API leveraged applications, we are looking at some kind of locally evolving AI that simply serve the local needs without the need for either investments or initiatives.

Small Teams - High Innovation aka the David Vs Goliath duels :??

What is the difference between an AI application and an Enterprise?Application ??Nothing in principle, except for the fact the?enteprise?application is an AI application with a lot of processes which do not yet leverage AI.?What the semantics do is that they tend to make the Enterprise App sound more than what it?actually is.?Where as, an AI Based workflow automation does the same with much shorter TATs and higher flexibility in terms.

So, a well formulated AI policy can actually help organizations and stakeholders get the best of small and highly tactical players instead of having to rely on behemoths for unique, small to medium scale enterprise requirements. ?

The dance of Priorities and Parameters:?

If conventional software is about digital acceleration of processes, AI is about priorities and letting the system take note of priority based action. This singular features of being able to pair a parameter with its priority is what makes AI an absolute game changer in the hands of those who understand clearly what is important in a given situation.

Unlike conventional software which takes forever to be incorporated with newer benchmarking requirements despite the most dynamic?devops, even the?most simplest?of AI codes can be grown exponentially simply by adding conditions and parameters.?So?in effect, you can take a face detection system and use the same thing to detect specific objects or changes in contours in a wide range of contexts.?

AI Friendly IoT Investments or IoT friendly AI Solutions :?

Why is AI important for planners and policy?makers ??Well, to?help them?avoid investing in?typewriters?when the computers are around the corner.??

True, it makes sense to have the legacy systems as well as some components of SCADA systems isolated from?vulnerable?IT systems in areas like Energy and Utilities, Power Grids et al.??

What if a city could avoid heavy investments in a Metro Transit System by enabling faster and?demand based?connections between commuters and existing public transport?fleets ???

Markets for AI or markets for Value ?

What does one mean by markets for AI when every piece of software can be?enhaced?with AI?features ??

What exactly is a market for?AI ??At best, AI is the initiation of a process based on an input. So, even the best of industry forecasts?are?bound to differ from reality??

because what we are seeing is the incorporation of AI Features into?exisiting?systems and processes with?stand alone?specialized software for very specific purposes.??

How could you define something like say AI applications in the domain of Security where it can be applied to private, national and industrial security applications.?The value, here is, what determines the market or the acquisition of it.

Domain wide transformation a.k.a Sweeping changes :

Except for the human intuition, all kinds of workflows that can be automated, can be further enhanced and a degree of autonomy can be granted to the systems themselves encompassing the functions of monitoring, detection and?rule based?action or?threshold based?responses. So, the data from machines and environment can be harnessed in ways that are contextual to the need of the day, the week, the season in addition to the overall workflow sanitization.??

The sheer scope of deployment will enhance moment to moment awareness of the machines as well as teams in charge of the operations. Imagine the applications in underground mining operations, energy and utilities, supply chain and logistics and you have can begin to make sense of the inputs emerging from the environment itself.??

What implications for human kind ? Health, security, amenities, services. You name it.

In clinical diagnostics alone, AI engines are being used to flag alert markers much faster than conventional legacy equipment. This means, any anomaly can be detected much earlier, paired with corelated markers for further analysis. We are talking about AI saving lives in multiple use cases in diagnosis alone.

Pitfalls the Policy makers should avoid:?

AI falls between an economic driver as well as a sphere of influence. Hence, policy makers are not only looking at newer forms of regulations and standards,?they?are also looking at a capability that has the potential to have sweeping effects over industries as well as specific interests.??

Pitfall Approach 1: AI is an enabler

Pitfall Approach 2: AI blueprints/roadmaps can be updated in the future

AI amplifies intelligence or the lack of it with equal intensity.

To simply look at AI as an enabler for monitoring and automation would be a strategic mistake. As stated earlier, AI is about the context, about the environment and about the situation and what the stakeholders want to do about it.?

Sensitizing the AI?Taskforce:?Context, Environment and Situation?

AI Task Forces can get mixed up in the flow of possibilities and updates from across the globe. Early adoption is a major competitive advantage only if the road maps are well thought out, inclusive of future requirements and adaptive to changes in the?particular ecosystems.??

While the roadmaps are to include the assets, the infrastructures and the alignment, the taskforces are to study and be on top of three fundamental abstract areas, which are most influential in determining the future of the AI.?China gets this extremely well.??

Context?:

The closest metaphor I can give to the relation between Context and AI is of the relation between Currency to its monetary value. Debates aside, Context is the single most influential concept that will determine the utility or futility of the AI Task Force.

To understand the significance of context, just consider the following:

1. Economic growth is a national interest
2. International Trade is subject to agreements among nations which include Financial systems and Technology standards
3. Industries are domestic economic drivers and a specific interest for each country

So, it pays to get the context right.

1. To have the overarching Context because all the components tend to influence each other.
2. To incorporate nuances into the context, i.e something that is not exactly measurable but influential like say the human capital to be expected from a younger population or the kind of investments in a city with an aging population.
3. The implications of the kind of changes that are likely to occur with the deployment of AI capabilities in the particular context are also of extremely high significance.

Environment?: Sensing it

AI is your eyes and ears and even super sensory to the extent that it can correlate pollution levels, traffic and even the time of the day.

"Sensing the environment" is a capability, that needs to be explicitly articulated in the Task Force. This is where, the teams can be phenomenally empowered with the kind of inputs that can make preventive actions faster and more effective. These kind of collated time series data maps can help formulate long term responses.

Environment Maps, or those policy makers who insist on them, have the biggest advantage in planning and leveraging infrastructure, making smart high coverage and low cost investments

Situation : Between two time frames ?

The best point of transition in any AI undertaking is by taking stock of the situation. If you were to cut down any AI undertaking or any AI requirement, the smallest unit be a situation, a SITREP, so to say. Anything else would make AI a meaningless vortex of data. Of course, there be many situations within the time frames, but even they have to be considered as situations to decentralize decision making to the last mile and the last meter.

Why ?

In AI as in life, the situation is between two time intervals, be it a recent interlude or a larger duration. Any report, any assessment or any component may be cut down into a situational unit for the entire thing to make sense. All the occurrences, the data from the environment, the exchanges of causes and effects, bracketed within the time frames are of primary significance in the process of updating priorities because Duh! what was relevant 2 years ago may remain relevant today, but with a different set of priorities.

Suffice to say, to all those PDFs that form the AI Roadmaps and Blue Prints, if they do not factor in the Context, the Environment and the Situations as the three Constant conceptual cascades, your entire AI game plan ought to be reviewed.

In a strange way, an AI taskforce's work is like that of a team in charge of finding the need and laying laying railway lines in a continent.

You need to have the awareness of the larger geography and the opportunities and the kind of a service that is most suitable in the area. Context.

You need to know about the terrain en route, the weather and what happens in the seasons. Environment

You need to connect the train to two points, to platforms between which travel makes the most sense. Situation.