Global Capability Centers( GCCs) are reflections of strategic components to parent organization’s business imperatives. GCCs are at an inflection point as the pace at which AI is changing every aspect is exponential and at high velocity. The rapid transformation and innovation of GCCs today is driven largely by ability for them to position AI strategic imperative for their parent organizations. AI is seen to the Trojan horse to catapult GCCs to the next level on innovation & transformation. In recent times; GCC story is in a changing era of value and transformative arbitrage.

Most of the GCCs are aiming towards deploying suite of AI led strategies to position themselves up as the model template of AI Center of Excellence. It is widely predicted that AI will disrupt and transform capability centers in the coming decades. How are Global Capability Centers in India looking at positioning themselves as model template for developing AI center of competence? How have the strategies of GCCs transformed with reference to parent organization? whilst delivering tangible business outcomes, innovation & transformation for parent organizations?

Strategic imperatives for GCC’s to consider to move incrementally in the value chain & develop and edge and start winning with AI:

AI transformation :

Artificial Intelligence has become the main focus areas for GCCs in India. The increasing digital penetration in GCCs across business verticals has made it imperative to focus on AI. Hence, GCCs are upping their innovation agenda by building bespoke AI capabilities , solutions & offerings. Accelerated AI adoption has transcended industry verticals, with organizations exploring different use cases and application areas. GCCs in India are strategically leveraging one of the following approaches to drive the AI penetration ahead –

• Federated Approach: Different teams within GCCs drive AI initiatives
• Centralized Approach: Focus is to build a central team with top talent and niche skills that would cater to the parent organization requirements
• Partner ecosystem : Paves a new channel for GCCs by partnering with research institutes , start-ups , accelerators
• Hybrid Approach: A mix of any two or more above mentioned approaches, and can be leveraged according to GCCs needs and constraints.
• Ecosystem creation : Startups /research institutes/Accelerators

One of the crucial ways that GCCs can boost their innovation agenda is by collaborating with start-ups, research institutes , accelerators. Hence, GCCs are employing a variety of strategies to build the ecosystem. These collaborations are a combination of build, buy, and partner models:

• Platform Evangelization: GCCs offer access to their AI platforms to start-ups
• License or Vendor Agreement: GCCs and start-ups enter into a license agreement to create solutions
• Co-innovate: Start-ups and GCCs collaborate to co-create new solutions & capabilities
• Acqui-hire: GCCs acquire start-ups for the talent & capability
• Research centers : GCCs collaborate with academic institutes for joint IP creation, open research , customized programs
• Joint Accelerator program : GCCs & Accelerators build joint program for customized startups cohort

To drive these ecosystem creation models, GCCs can leverage different approaches. Further, successful collaboration programs have a high degree of customization, with clearly defined objectives and talent allocation to drive tangible and impact driven business outcomes.

Differentiated AI Center of Capability :

GCCs are increasingly shifting to competency, capability creation models to reduce time-to-market. In this model, the AI Center of Competence teams are aligned to capability lines of businesses where AI center of competence are responsible for creating AI capabilities, roadmaps and new value offerings, in collaboration with parent organization’s business teams. This alignment and specific roles have clear visibility of the business user requirement. Further, capability creation combined with parent organization’s alignment helps in tangible value outcomes. In several cases, AI teams are building new range of innovation around AI based capabilities and solutions to showcase ensuing GCC as model template for innovation & transformation. GCCs need to conceptualize a bespoke strategy for building and sustaining AI Center of Competence and keep it up on the value chain with mature and measured transformation & innovation led matrices.

AI Talent Mapping Strategy:

With the evolution of analytics ,data sciences to AI, the lines between different skills are blurring. GCCs are witnessing a convergence of skills required across verticals. The strategic shift of GCCs towards AI center of capability model has led to the creation of AI, data engineering & design roles. To build skills in AI & data engineering, GCCs are adopting a hybrid approach. The skill development roadmap for AI is a combination of build and buy strategies. The decision to acquire talent from the ecosystem or internally build capabilities is a function of three parameters – Maturity of GCC s existing AI capabilities in the desired or adjacent areas ,Tactical nature of skill requirement & Availability and accessibility of talent in the ecosystem. There’s always a heavy Inclination towards building skills in-house within GCCs and a majority of GCCs have stressed upon that the bulk of the future deployment in AI areas will be through in-house skill-building and reskilling initiatives. However, talent mapping strategy for building AI capability is a measured approach else can result in being a Achilles heel for GCC and HR leaders. 

GCCs in India are uniquely positioned to drive the next wave of growth with building high impact AI center of competence , there are slew of innovative & transformative models that they are working upon to up the ante and trigger new customer experience , products & services and unleash business transformation for the parent organizations. This will not only set the existing GCCs on the path to cutting-edge innovation but also pave the way for other global organizations contemplating global center setup in India.AI is becoming front runner to drive innovation & transformation for GCCs. 

“Enabling clients reimagine their decision making & accentuate the business performance with AI strategy in a transformation, innovation and disruption driven world”

In today’s fast paced & volatile VUCA world, leaders face unprecedented challenges. They need to navigate through volatility while staying focused on strategy, business performance and culture.  Artificial Intelligence is fast becoming a game changing catalyst and a strategic differentiator and almost a panacea to solve large, complex and unresolved problems.  To be an AI powered organization, leaders not only need to have a broad understanding of AI strategy, they need to know how and where to use it.  AIQRATE advisory services and consulting offerings are designed to enable leaders and decision makers from Enterprises, GCCs, Cloud Providers, Technology players, Startups, SMBs, VC/PE firms, Public Institutions and Academic Institutions to become AI ready and reduce the risk associated with curating, deploying AI strategy and ensuing interventions and increase the predictability of a durable leader’s success.

In the age of the bionic enterprises, AI continues to dominate the technology & business landscape.  Under the aegis of transformation, disruption and innovation, AI has several applications and impact areas which usher a new change in how we make decisions in the enterprise and personal spheres.  Traditionally, human decisions are to a large extent based on intuition, gut and historical data.  In the age of AI, several of our decisions will be taken by algorithms.  Leveraging AI, the ability to mimic the human brain and the ensuing ability to sense, comprehend and act will significantly go up and will result in emergence of augmented intelligence in decision making. Enterprises, GCCs, SMBs, Startups and Government Institutions are attempting to harness the power of AI to change the way they do business.  All these industry segments are looking at AI becoming the secret sauce behind making them gain a competitive advantage.  If you have not started yet, you are already behind the competition, however large or pedigreed you might be.

So, where are you placed on your AI journey?  At AIQRATE, we can guide you on your journey of understanding what AI can do for you, embedding it within your business strategy, functional areas and augmenting the decision-making process.

At AIQRATE, we are here to help you with the art of the possible with AI.  Through our bespoke AI strategy frameworks, methodologies, toolkits, playbooks and assessments, we will bring seamless Transformation, Innovation and Disruption to your businesses.  Leveraging our proven repository of consulting templates and artifacts, we will curate your AI strategic approach roadmap. Our advisory offerings and consulting engagements are designed in alignment with your strategic growth, vision and competitive scenarios.

We are at an inflection point where AI will revolutionize the way we do business. The paradigms of customer, products, offerings, services and competition will change dramatically; and being AI-ready will become a true differentiator.  AIQRATE will be your strategic partner to help you to prepare for what’s next in order to stay relevant.

Enclosing here our journey walk through of 2020.

For more than a decade, Silicon Valley’s technology investors and entrepreneurs obsessed over social media and mobile apps that helped people do things like find new friends, fetch a ride home or crowdsource a review of a product or a movie.

Robots after the “Like” Button

Now Silicon Valley has found its next shiny new thing. And it does not have a “Like” button.

The new era in Silicon Valley centers on artificial intelligence and robots, a transformation that many believe will have a payoff on the scale of the personal computing industry or the commercial internet, two previous generations that spread computing globally. Computers have begun to speak, listen and see, as well as sprout legs, wings and wheels to move unfettered in the world.

The shift was evident in a Lowe’s home improvement store here this month, when a prototype inventory checker developed by Bossa Nova Robotics silently glided through the aisles using computer vision to automatically perform a task that humans have done manually for centuries.

The robot, which was skilled enough to autonomously move out of the way of shoppers and avoid unexpected obstacles in the aisles, alerted people to its presence with soft birdsong chirps. Gliding down the middle of an aisle at a leisurely pace, it can recognize bar codes on shelves, and it uses a laser to detect which items are out of stock.

Silicon Valley’s financiers and entrepreneurs are digging into artificial intelligence with remarkable exuberance. The region now has at least 19 companies designing self-driving cars and trucks, up from a handful five years ago. There are also more than a half-dozen types of mobile robots, including robotic bellhops and aerial drones, being commercialized.

The Surge after the Static – The Social Way

There has been a slow trickle in investments in robotics all this while, and suddenly, there seem to be a dozen companies securing large investment rounds focusing on specific robotic niches. Funding in A.I. start-ups has increased more than fourfold to $681 million in 2015, from $145 million in 2011, according to the market research firm CB Insights. The firm estimates that new investments will reach $1.2 billion this year, up 76 percent from last year.

By contrast, funding for social media start-ups peaked in 2011 before plunging. That year, venture capital firms made 66 social media deals and pumped in $2.4 billion. So far this year, there have been just 10 social media investments, totaling $6.9 million, according to CB Insights. Last month, the professional social networking site LinkedIn was sold to Microsoft for $26.2 billion, underscoring that social media has become a mature market sector.

Even Silicon Valley’s biggest social media companies are now getting into artificial intelligence, as are other tech behemoths. Facebook is using A.I. to improve its products. Google will soon compete with Amazon’s Echo and Apple’s Siri, which are based on A.I., with a device that listens in the home, answers questions and places e-commerce orders. Satya Nadella, Microsoft’s chief executive, recently appeared at the Aspen Ideas Conference and called for a partnership between humans and artificial intelligence systems in which machines are designed to augment humans.

The auto industry has also set up camp in the valley to learn how to make cars that can do the driving for you. Both technology and car companies are making claims that increasingly powerful sensors and A.I. software will enable cars to drive themselves with the push of a button as soon as the end of this decade — despite recent Tesla crashes that have raised the question of how quickly human drivers will be completely replaced by the technology.

AI Outdoes the Silicon Valley Reset Trend

Silicon Valley’s new A.I. era underscores the region’s ability to opportunistically reinvent itself and quickly follow the latest tech trend. This is at the heart of the region’s culture that goes all the way back to the Gold Rush. The valley is built on the idea that there is always a way to start over and find a new beginning.

The change spurred a rush for talent in A.I. that has become intense. It is unusual that the number of people trying to get the students to drop out of the class halfway through because now they know a little bit of this stuff is crazy. The valley’s tendency toward reinvention dates back to the region’s initial emergence from the ashes of a deep aerospace industry recession as a consumer-electronics manufacturing center producing memory chips, video games and digital watches in the mid-1970s. A malaise in the personal computing market in the early 1990s was followed by the World Wide Web and the global expansion of the consumer internet.

A decade later, in 2007, just as innovation in mobile phones seemed to be on the verge of moving away from Silicon Valley to Europe and Asia, Apple introduced the first iPhone, resetting the mobile communications marketplace and ensuring that the valley would — for at least another generation — remain the world’s innovation center.

In the most recent shift, the A.I. idea emerged first in Canada in the work of cognitive scientists and computer scientists like Geoffrey Hinton, Yoshua Bengio and Yann LeCun during the previous decade. The three helped pioneer a new approach to deep learning, a machine learning method that is highly effective for pattern recognition challenges like vision and speech. Modeled on a general understanding of how the human brain works, it has helped technologists make rapid progress in a wide range of A.I. fields.

The Road Ahead

How far the A.I. boom will go is hotly debated. For some technologists, today’s technical advances are laying the groundwork for truly brilliant machines that will soon have human-level intelligence. Yet Silicon Valley has faced false starts with A.I. before. During the 1980s, an earlier generation of entrepreneurs also believed that artificial intelligence was the wave of the future, leading to a flurry of start-ups. Their products offered little business value at the time, and so the commercial commercial enthusiasm ended in disappointment, leading to a period now referred to as the “A.I. Winter.” The current resurgence will not fall short this time, and the economic potential in terms of new efficiency and new applications is strong.

There has been a great deal of talk about the use of Artificial Intelligence chatbots in the last few weeks, especially given the news that Facebook are looking to implement AI into their Messenger and WhatsApp platforms, which are currently used by more than 1.8 billion people worldwide. However, does this bode well for the relationship between humans and Artificial Intelligence programs? Would you rather speak to an intelligent algorithm rather than a fellow human being?

The Sales and Customer Support Bot-ler ?

Chatbots, done right, are the cutting-edge form of interactive communications that captivate and engage users. But what kind of potential do they have for sales & customer support ?

To answer this, I should emphasize that customer service can be a delicate field. A lot of consumer engagement with a company happens when something goes wrong — such as a recently-purchased broken product or an incorrect bill or invoice.

By nature, these situations can be highly emotional. And as a business, you want to be responsive to potentially problematic customer inquiries like these. So relying on a chatbot to resolve issues that require a human touch might not be the best idea.

This is especially true if you let your bot “learn” from interactions it sees (say, in user forums) with no or minimal supervision. Things can easily go wrong, as the disaster around Microsoft’s Twitter bot “Tay” showed.

On the other hand, with the right supervision and enough training data, machine learning as an A.I. technique can help build very responsive and accurate informational chatbots — for example those that are meant to help surface data from large text collections, such as manuals.

I’d say that machine learning as a technique has been shown to work best on image processing. The advancements that Google, Facebook, and innovative startups such as Moodstocks (just acquired by Google) are showing in that space are truly amazing. Part of the amazement however, comes from the fact that we now see software take on another cognitive task that we thought could only be managed by humans.

What can bots do for the bottom line?

In my opinion, a bot’s primary application lies in customer service since most companies unfortunately continue to rely on an ancient methodology to manage customer interaction. And this is to be expected as most consumers themselves are still “hard-wired” to pick up a phone and dial a number when they want to engage with a company.

Companies haven’t necessarily made it easy for consumers to transition to digital-first interaction. Consumers are forced to either download a mobile app, browse websites, or use voice, the “dumbest” channel the smartphone has to offer, to retrieve information or perform transactions.

This is truly unfortunate because when it comes to paying a bill, checking on an order status, or reviewing account transactions, nothing is easier than sending a simple message. And with 900 million users now on Facebook Messenger, 1 billion on WhatsApp, and hundreds of millions more on basic SMS, companies have a consumer-preferred new medium for engaging with customers.

With messaging, a simple question can be posed in a simple message such as “Where is my order?”

Contrast this to the conventional options of being forced to shepherding that question through a maze of web or mobile app menus, or with IVR systems over the phone. Now imagine how a consumer-adopted, digital and automated interaction for simple questions vs. agent interaction over the phone could impact customer service and its cost. When chatbots handle the most commonly-asked questions, agent labor is reduced or redeployed to manage more complex and time-consuming interactions. Simple and moderate issues are resolved faster, leading to greater customer satisfaction and long-term loyalty. Bots can help deflect calls from the contact center and your IVR, which further reduces speech recognition license and telephony cost.

Could there be Bot-tle-necks?

There is also the question of whether these chatbots will take jobs from humans; a subject of fierce debate for all industries and levels in the last few months. Facebook itself has been quick to clarify that these chatbots are not going to replace the people in their organisation, but instead to work alongside them. For example, Facebook have said that the customer service executives will be required to train the AI bots, and to step in when the AI comes unstuck, which is likely to be fairly frequently in the early stages! Chinese messenger service WeChat has taken the chatbot idea on, with companies having official accounts through which they are able to communicate with their customers. However, the platform is still in its early stages, and is reported to be incredibly frustrating to use, so those in the customer service sector needn’t worry that their jobs are under threat quite yet!

While we might see chatbots starting to appear through the likes of Facebook Messenger and WhatsApp platforms in the coming 12 months, and will be dedicating teams of engineers to train the platforms, rather than relying on the general public. There are three main factors on which their success depends.

The first is with how much freedom AI in general is allowed to be developed, especially given the hesitation that the likes of Elon Musk and Bill Gates have about a potential ‘Singularity’, with Musk recently being quoted as saying that ‘Artificial Intelligence is our biggest existential threat’.

The second is arguably more important; how willing the general public are to help develop the chatbots, by having conversations with them, in the knowledge that they are talking to an autonomous entity.

More important still, are these chatbots going to be safe from cyberattacks? How will you know if your financial information will be secure if you disclose it to a chatbot, especially if there are unlikely to be the same multi-stage security checks that are the hallmark of P2P customer service interactions?

The Road Ahead?

Many companies are already launching bots for customer acquisition or customer service. We will see failures, and in parts, have already seen some. Bots are not trivial to build: you need people with experience in man-machine interface design. But to quote Amara’s Law: “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”

Bots are here to stay, and will be a great new platform and make things easier for all of us. But bots that try to do too much or set unreasonable expectations will slow consumer confidence and acceptance of them. What might help us now is maybe to calm down a bit with the hype, and focus on building good bots that have value — then share our experiences, and show the world where the true value lies.