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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.

Across the world of technology, we are seeing the proliferation of new age developments across software and hardware – titled “Exponential Technologies”. The term refers to a wide range of recent technology breakthroughs – Artificial Intelligence, Internet of Things, Cloud Computing, Augmented and Virtual Reality, Blockchain and the allied. They are collectively referred to as ‘exponential’ considering the humungous potential value that they could possibly add to business. As these technologies continue to mature in their development and adoption, the world is gaining a more concrete insight into the worth of these technologies and their use cases. 2019 will most certainly be the year where these technologies will go mainstream – and deliver exponential value to their proponents. With high investor interest (and money) riding on these new age technologies, I am confident that in 2019, there will be a high uptake in their commercialization. Here are the top10 trends that I foresee in 2019 in exponential technologies :

1. Blockchain Beyond the Hype

In 2018, there was no doubt a lot of excitement and buzz as technology vendors and investors started investigating blockchain and cryptocurrency. In 2019, expect blockchain to move beyond the hype and enter the mainstream. Gartner estimates that blockchain applications will create $3.1 trillion in business value by 2030. Over 2018, several tech-savvy businesses started their own experiments with blockchain in areas such as supply chain, which is ripe for a blockchain-powered disruption. Within blockchain, I foresee:

Increased collaboration between businesses and tech vendors to unlock the power of blockchain across multiple use cases. Given its immutable and decentralized nature, blockchain will be invaluable in sectors such as manufacturing, defense and financial services – and we will see innovative use cases coming out of these domains

Within blockchain, smart contracts specifically will gain immense traction. The business value of smart contracts is remarkably clear – they drastically reduce the time and effort for routine but lengthy paperwork processes, while maintaining the sanctity through a blockchain network

Due to the numerous crypto frauds seen uncovered in the last year, more and more sovereign governments will push legislation to regulate and establish clear rules around blockchain and cryptocurrency. I have no doubts that this will have a net positive impact – as it will demonstrably improve the consumer confidence and enterprise adoption for these technologies by laying down a clear legal framework for their use

2. 3rd Platform Technology to Accelerate Digital Transformation

A combination of social, mobile, data-driven decision-making and cloud infrastructure and processing is commonly referred to today as 3rd platform technology. In 2019, there will be no stopping the juggernaut of internal IT departments moving ever faster towards digital technology.

According to a research by IDC, it is expected that by 2023, 75% of all IT spending will be on such 3rd platform technology, with over 90% of all enterprises building “digital native” IT environments

Further advanced technologies such as distributed cloud, hyperagile app technologies and architectures, AI at the edge and AI-powered voice UIs will be central to how enterprises enable digital transformation using 3rd platform technologies.

This expansion in demand for 3rd platform technologies will be the outcome on increasing pressures on internal IT to become profit centers and unlocking new sources of revenue for the parent enterprise. Using easily scalable and replicable digital frameworks, early adopter IT departments would be able to commercialize this technologies to their competitors while giving their businesses critical competitive advantage

3. Quantum Computing to Come of Age

Quantum computing is a non-traditional form of computing operating on the quantum state of subatomic particles and representing information as elements denoted through quantum bits. The unmitigated rise in the development and permeation of quantum computing is the third key trend that I see for 2019. It is estimated that by 2023, 20% of organizations will carve out budgets for quantum computing projects, as opposed to less than 1% today.

 With heavier software paradigms such as Internet of Things, Artificial Intelligence and blockchain achieving mainstream status, there will be large scale demand for quantum computing to come out of the shadows of academia and into business. Quantum computing will move well beyond a buzzword and will be part of multiple projects at an experimental scale at corporations.

Quantum Computing will succeed where traditional computing has failed, providing parallel execution and exponential scalability. Such systems will take on problems too complex for a traditional approach or where the latency for traditional algorithms would be untenable

Business leaders across multiple industries – automotive, financial, insurance, pharmaceuticals, military and research organizations – will see massive gains through the advancements in Quantum Computing .

 4.Acceleration in the Pervasiveness of the Internet of Things

While Internet of Things has demonstrably hit mainstream status across industries such as consumer goods and retail, and use cases such as supply chain and logistics, we will see further acceleration in its adoption in 2019

 IOT-enabled hardware devices will proliferate nearly all walks of human life. Devices from sensors, wearables, smart assistants and wearables will be a feature in everyday life for most individuals in the developed world and will be a key focus for powering digital transformation

With increasing demand for IOT-powered devices across use cases will definitively bring endpoint security into focus for enterprises. As IOT devices become the first frontier for communication with consumers through highly sensorized environments, we will see a rapid escalation in the adoption of endpoint security practices and software

To support this deep network of the Internet of Things will require an immediate focus on rapidly enabling 5G connectivity in 2019. Not having a robust underlying infrastructure to support IOT will be disastrous for businesses and individuals who will be highly reliant on it for their day-to-day activity.

 5. Convergence of AI, Blockchain, Cloud and IO

Could a future software stack comprise AI, Blockchain and IOT running on the cloud? It is not too hard to imagine how these exponential technologies can come together to create great value. In 2019, I expect that we will see a strong spread of use cases that effectively combine these technologies.

Internet of Things devices will largely be the interface with which consumers and other societal stakeholder will interact. Voice-enabled and always connected devices – such as Google Home and Amazon’s Alexa will augment the customer experience and eventually become the primary point of contact with businesses

Artificial Intelligence frameworks such as Speech Recognition and Natural Language Processing are making huge advances. These will be the translation layer between the sensor on one end and the deciphering technology on the other end

Blockchain-like decentralized databases will act as the immutable core for managing contracts, consumer requests and transactions between various parties in the supply chain

Cloud will be the mainstay for running these applications requiring huge computational resources and very high availability. I expect more cloud vendors to come forward (Amazon and Google for instance already have) with specialized cloud frameworks to handle the torrent of requests that these type of applications would require.

6.New UI/UX Interfaces to Emerge on the Scene

To unlock and harness the true value of exponential technology it is incumbent that we do not rely only on existing paradigms of end-user interfaces such as web and mobile. We need to reinvent new paradigms and explore game changing new interfaces that will help usher better customer and user experiences.

 Conversational platforms – ones which are primarily activated through voice and voice-recognition AI will conduct numerous exchanges on behalf of customers. Already we are seeing rapid adoption of conversational interfaces such as Google Home, Amazon Alexa and Apple’s Siri. These will only grow and prominence and entire CX use cases will be centered around these platforms

Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) will be increasingly leveraged across a vast selection of topical use cases. Incorporating these alongside traditional interfaces will be crucial to delivering the future of an immersive user experience. According to Gartner, we will shift from thinking about individual devices and fragmented user interface (UI) technologies to a multichannel and multimodal experience.

These immersive experience-led interfaces such as VR and AR will become increasingly popular, with 70% of enterprises experimenting with such technology for consumer and enterprise use and 25% of organizations deploying it into production.

7.Edge Computing to become an Enterprise Mandate

Simply put, edge computing is a computing topology in which information processing, and content collection and delivery, are placed closer to these endpoints. For reducing the latency running AI algorithms and eventual response times, edge computing will become an enterprise mandate for use cases involving a convergence of IOT and AI.

In 2019, adoption of edge computing will be driven by the need to keep the processing power close to endpoints as opposed to a centralized cloud server. Having said that, edge computing will not necessitate the creation of a new architecture. Cloud and edge computing will complement each other. Cloud services will be charged with centralized service execution, not only on centralized servers, but also across distributed servers on-premises and on-the-edge devices themselves.

Five years down the line expect to see specialized AI chips, supporting greater processing power, storage and other advanced capabilities. They will be incorporated into a wider array of edge devices. Not too far into the future, we will see 40% of organizations’ cloud deployments include an element of edge computing and 25% of endpoint devices and systems will execute AI algorithms.

We will see more intelligent and empowered edge computing devices as well. According to Gartner, storage, computing and advanced AI and analytics capabilities will expand the capabilities of edge devices through 2028.

8. DevOps Augmented by AI

Despite almost universal acceptance of the DevOps framework across global enterprises, adoption has been patchy and slow. This is due to numerous reasons, ranging from a distributed toolset and a paucity of expert practitioners. However with the emergence of AI, we will see an increased process automation between software development and deployment, accelerating the enablement of DevOps

AI-powered QA suites will increase the automation quotient in the DevOps process. Given the advancements seen in automation, AI will rapidly intervene in the QA process across unit testing, regression testing, functional testing and user acceptance testing.

DevSecOps will combine the power of DevOps and AI in the field of information security. A centralized logging architecture recording suspicious activity and threats combined with ML-based anomaly detection techniques will empower developers to accurately pinpoint potential threats to their system and secure it for the future.

AI will also break the cultural barriers that typically exist between developer and operations teams. . AI-powered systems will enable DevOps teams to have a single, unified view into system issues across a complex toolchain while improving the collective knowledge of anomalies detected and the pathways for redressal.

 9.Autonomous Things on the Rise:

At present, we are seeing experiments at an advanced level in the field of autonomous things. Autonomous things comprise whole gamut of unmanned objects – from drones, cars and robots. In 2019, I expect there to be a steady rise in the adoption and appreciation of this area of technology

 Autonomous things of today are largely centered around the current paradigm of basic automation and rigid if-else programming rules. The next revolution in the field of autonomous things will be by exploiting the power of AI to exhibit more advanced, proactive and multi-threaded behaviors

Demand for autonomous things will continue to grow, specifically for autonomous vehicles. According to a Gartner survey, by 2021, 10% of new vehicles will have autonomous driving capability, compared to less than 1% in 2017.

Robotics and drones powered by AI will be able to address more complex use cases bringing in further efficiencies to incumbent businesses in the field of logistics delivery, warehouse management and manufacturing

10. AI to Disrupt Cybersecurity

Finally, the last key trend in the exponential technologies space for 2019 pertains to cybersecurity. While this is a remarkably advanced field, we will see continued growth and evolution of cybersecurity in combination with artificial intelligence

 Using anomaly detection and machine learning, AI will hugely disrupt the field of cyber security. Security practitioners will be empowered to identify intrusions and malafide behavior faster using automated, always-on algorithms to constantly survey the secured network for wrongful activity and address concerns before they break-ins occur

AI can be quickly training over a massive data set of cyber security, network, and even physical information. Cyber security vendors will soon roll out AI-enabled solutions that will learn at an abstract level to detect and block abnormal behavior, even when this behavior does not fit within a known pattern. I expect that in 2019 companies will incorporate ML into every category of cybersecurity products.

By extension, we will see a fight between good AI and bad AI in the domain of cybersecurity. There are genuine fears that the next generation of attacks will not be carried out by human hackers but pieces of code designed to rapidly infiltrate a secure environment. Countering that with so-called ‘good AI’ will be crucial in undermining the impact these fast-paced attacks can have

The year 2018 will be remembered as the year that artificial intelligence stopped being on the periphery of business and entered the mainstream realm. With increasing awareness and capability of AI among the numerous stakeholders, including tech buyers, vendors, investors, governments, and academia, I expect AI will go beyond just tinkering and experiments and will become the mainstay in the business arena.

With an increasing percentage of these stakeholders professing their commitment to leveraging this technology within their organisations, AI has arrived on the world scene. We are sure to see transformative business value being derived through AI in the coming years. As we come to the close of 2018, let us gaze into the crystal ball to see what 2019 will hold for this game-changing technology:

The rise of topical business applications

Currently, we have a lot of general purposes AI frameworks such as Machine Learning and Deep Learning that are being used by corporations for a plethora of use cases. We will see a further evolution of such technology into niche, topical business applications as the demand for pre-packaged software with lower time-to-value increases. We will see a migration from the traditional AI services paradigm to very specific out-of-the-box applications geared to serve particular use cases. Topical AI applications in this space that serve such use cases will be monumentally useful for furthering the growth of AI, rather than bespoke services that require longer development cycles and may cause bottlenecks that enterprises cannot afford.

The merger of AI, Blockchain, cloud, and IoT

Could a future software stack comprise AI, Blockchain, and IoT running on the cloud? It is not too hard to imagine how these exponential technologies can come together to create great value. IoT devices will largely be the interface with which consumers and other societal stakeholders will interact. Voice-enabled and always connected devices – such as Google Home and Amazon’s Alexa – will augment the customer experience and eventually become the primary point of contact with businesses. AI frameworks such as Speech Recognition and Natural Language Processing will be the translation layer between the sensor on one end and the deciphering technology on the other end. Blockchain-like decentralised databases will act as the immutable core for managing contracts, consumer requests, and transactions between various parties in the supply chain. The cloud will be the mainstay for running these applications, requiring huge computational resources and very high availability.

Focus on business value rather than cost efficiency

2019 will finally be the year that majority of the executive and boardroom conversations around AI will move from reducing headcount and cost efficiency to concrete business value. In 2019, more and more businesses will realise that focusing on AI solutions that reduce cost is a criminal waste of wonderful technology. Ai can be used to identify revenues lost, plug leakages in customer experience, and entirely reinvent business models. I am certain that businesses that focus only on the cost aspect will stand to lose ground to competitors that have a more cogent strategy to take the full advantage of the range of benefits that AI offers.

Development of AI-optimised hardware and software

Ubiquitous and all-pervasive availability of AI will require paradigm shifts in the design of the hardware and software that runs it. In 2019, we will see an explosion of hardware and software designed and optimised to run artificial intelligence. With the increasing size and scale of data fueling AI applications and even more complex algorithms, we will see a huge demand for specialised chipsets that can effectively run AI applications with minimal latency. Investors are showing heavy interest in companies developing GPUs, NPUs, and the like – as demonstrated by Chinese startup Cambricon, which stands valued at a whopping $2.5 billion since its last round of funding this year. End-user hardware such as smart assistants and wearables will also see a massive increase in demand. Traditional software paradigms will also continue to be challenged. Today’s novel frameworks such as TensorFlow will become de rigueur. Architectural components such as edge computing will ensure that higher processing power is more locally available to AI-powered applications.

‘Citizen AI’ to be the new normal 

One of the reasons we saw widespread adoption of analytics and data-driven decision-making is because we built applications that democratised the power of data. No longer was data stuck in a remote silo, accessible only to the most sophisticated techies. With tools and technology frameworks we brought data into the mainstream and made it the cornerstone of how enterprises plan and execute strategy. According to Gartner, the number of citizen data scientists will grow five times faster than the number of expert data scientists. In 2019, I expect Citizen AI to gain traction as the new normal. Highly advanced AI-powered development environments that automate functional and non-functional aspects of applications will bring forward to a new class of “citizen application developers”, allowing executives to use AI-driven tools to automatically generate new solutions.

Policies to foster and govern AI

Following China’s blockbuster announcement of a National AI Policy in 2017, other countries have rushed to share their take on policy level interventions around AI. I expect to see more countries come forward with their versions of a policy framework for AI – from overarching vision to allaying concerns around ethical breaches. At the same time, countries will also be asked to temper their enthusiasm of widespread data proliferation by releasing their own versions of GDPR-like regulations. For enabling an ecosystem where data can be used to enrich AI algorithms, the public will need to be convinced that this is for the overall good, and they have nothing to fear from potential data misuse and theft.

Speech Recognition will revolutionise NLP

In the last few years, frameworks for Natural Language Understanding (NLU) and Natural Language Generation (NLG) have made huge strides. NLP algorithms are now able to decipher emotions, sarcasm, and figures of speech. Going forward, voice assistants will use data from voice and combine that with deep learning to associate the words spoken with emotions, enriching the overall library that processes speech and text. This will be a revolutionary step forward for fields such as customer service and customer experience where many bots have typically struggled with the customer’s tone of voice and intonation.

The growth of explainable AI

And finally, with numerous decisions powered by AI – and specifically unsupervised learning models – we will see enterprises demand “explainable” AI. In simplified terms, explainable AI helps executives “look under the hood” to understand the “what” and “why” of the decisions and recommendations made by artificial intelligence. Development of explainable AI will be predicated on the need for increased transparency and trust. Explainable AI will be essential to ensure that there is some level of transparency (and potentially, learning) that is gleaned from unsupervised systems.

Convergence of AI and analytics

This is a trend that is a logical consequence of the decisive power of data in business today. In 2019, we will see a merger of analytics and AI – as the one-stop for uncovering and understanding insights from data. With advancements in AI seen so far, the algorithms are more than capable of taking up tasks that involve complex insight generation from multi-source, voluminous data. This convergence of AI and analytics will lead to automation that will improve the speed and accuracy of the decisions that power business planning and strategy. AI-powered forecasting will help deliver faster decisions, with minimal human interventions and create higher cost savings for the business.

Focus on physical and cybersecurity paradigms

Two of the domains ripe for an AI transformation are the fields of physical and cybersecurity. As intrusions into physical and virtual environments become commonplace and threats become hugely pervasive, AI will be a massive boost to how we secure these environments. Advances in fields such as ML-powered anomaly detection will drastically reduce the time required to surface potential intrusions into secure environments. This will enable organisations to better protect user data. When combined with Blockchain, AI will give cybersecurity a huge boost through decentralised, traceable databases containing valuable client and strategic information. On the physical security side, Computer Vision is rapidly gaining currency in the fields of physical intruder detection. Surveillance cameras, originally manned by security guards, will soon be replaced by AI-powered systems that will be able to react faster and more proactively to intruders that pose a threat to physical premises. When you combine that with face recognition, working with a database of known offenders, we will see a quantum drop in the time required to adjudicate and address cases of theft and unauthorised entry by law enforcement agencies.

In summary, the broad directions that I predict AI will take include interventions to make it more embedded, responsible, and explainable; convergence with other exponential technologies such as cloud, Blockchain, and IoT; cybersecurity; a greater proliferation and development of use cases; and great strides in the technology and its supporting infrastructure. Enterprises would do well to adopt this revolutionary technology and ensure a strong availability of talent to conceptualise, develop, and unleash value from AI applications.