The world is changing at an accelerated pace, thanks to exponential technologies like AI, IoT, automation, and Blockchain. Cloud computing, AR, VR, and ubiquitous smartphones are other drivers of tech change. The impact of these architecture stacks is discussed in the new publication, Wiley Innovation Black Book on Exponential Technologies, released by Wiley India.
The material is spread across 344 pages, with contributions by 17 tech practitioners from India. The book series editor is Sameer Dhanrajani, Chief Strategy Officer at Strategy Analytics. His other book is AI and Analytics: Accelerating Business Decisions (see my book review here).
Unfortunately, there is no executive summary or introductory chapter that ties together key themes from each chapter and shows how they inter-connect. There is lots of repetition across the chapters, and some of them are full of general speculation without a single case study or example.
Here are some of my key takeaways from the material, also summarised in Table 1 (below). See my reviews of the related books as well: Machine, Platform, Crowd; The AI Advantage; Human + Machine; The Subscription Economy; The Inevitable; The Four; and Industries of the Future.
The book begins with a classic quote by Ray Kurzweil, explaining what exponential change in technology implies: “If I take 30 steps linearly, I get to 30. If I take 30 steps exponentially, I get to a billion.”
Machine strengths are speed, accuracy, repetition, resilience, predictive capabilities, and scalability. Human strengths, on the other hand, are creativity, agility, dexterity, improvisation, judgment, and social and leadership abilities. Companies need to find ways of balancing these two sets of abilities via augmentation.
AI technologies available now include ML, deep learning, chatbots, NLP, pattern recognition, and autonomous systems. The next wave of AI will feature thought-controlled robots, neuromorphic computing, surgical robots, real-time universal translation, and virtual companions.
Deep Thomas, of Aditya Birla Group, classifies the AI maturity stages of different industries: leaders (ICT, finance), advanced (retail, health), experimental (automotive, industrial equipment), emerging (chemicals, energy) and laggards (F&B, mining, agriculture). The industrial revolution has passed through three stages: steam, electricity, and simple digitisation, and we are now in Industry 4.0.
Manufacturing impacts due to tech innovation are in operational excellence (Mercedes, Fanuc, GM), superior customer experience (Lenovo, Komatsu), new business models (Volvo, Uber), and agile product development (GE Appliances FastWorks). Digital twins, collaborative machines, and additive manufacturing can improve manufacturing process efficiency (MPE) and predictive asset maintenance (PAM).
“Robots will automate dull, dirty and dangerous tasks,” Deep writes. Supply chains will become self-healing and resilient. Micro-factories and nano-materials are other developments to watch.
Wearables and AR will transform training of operators. Worker safety and security will be improved, but they also need to be upskilled as the factory of the future will be built on the “Internet of Abilities.” Industries will need to become sustainable via reuse, recycle, reclaim, recover, and remanufacture approaches.
Ajay Kelkar, Co-founder of Hansa Cequity, explains that turbulence and disruption are much more a part of a chief marketing officer’s life today than ever before. The challenge is to achieve customer intimacy via automation at scale, in real-time. Customer research is becoming more tech-centric, and many companies are becoming “datavores”.
Companies need to align the internal cultures of departments such as IT (reliability, continuity) and marketing (innovation, change). Digital media have given consumers a “social megaphone,” and new metrics are needed to prove return on marketing investment (RoMI) of campaigns.
Customers seem willing to share data in return for value addition and relevant services. But challenges include ensuring data privacy, while also competing with the likes of Amazon, Google, and Facebook.
Anees Merchant, of Course5 Intelligence, shows how rental and subscription models are transforming the media industry. Consumers are more demanding, and the work-life distinction is blurring. Corporate challenges lie in moving from pockets of capability to end-to-end solutions.
Creative inputs from AI are emerging in content cataloguing and summarisation, macro- and micro-packaging, script generation, revenue predictions, and digital asset management. Trends to watch are holograms and nano-robotics.
Pramod Singh, of Envestnet | Yodlee, highlights the importance of banking-fintech partnerships. Enriched transaction data along with behaviour pattern analysis can enable hyper-personalisation of services. Governments can stimulate and incentivise the ecosystem as well.
“The rate of innovation in technology has given InsureTech an unprecedented impetus,” writes Anshu Sharma Raja of Standard Chartered Bank. Millennials prefer digital channels to purchase insurance, and the rise of autonomous cars poses new questions on who should be buying accident insurance.
Connected cars and real-time monitoring via IoT are transforming insurance practices in transportation. Consumer wearables provide new data to measure the price of risk. Companies need to integrate “stove piped” databases across sub-disciplines. “To meaningfully participate in the platform economy, insurers must embrace ecosystems and be prepared to partner with competitors, other industries, and innovation technology-based service providers,” Anshu advises.
Ashish Singru, from eBay’s Bangalore office, traces the rise of retail tech transformations via SPSS, barcodes, and SQL, as well as business models such as special category stores and loyalty programmes. Today, ML helps deal with the breadth and depth dimensions of data of high volume, variety and velocity.
Search, browse, recommendations and deals are now part of the omni-channel experience. Customer expectations have shot up, and ecommerce players need to anticipate customer needs, empower them, and curate the experience. Ecommerce seems to lead in touch, physical retail in ‘touch.’ Trends to watch are visual search and AI-powered shelf-space arrangement.
Atul Jalan, Founder and CEO of Manthan, explains that the best technology is smart enough to absorb its own complexity. Truly disruptive technologies change our behaviour without our even knowing about it. “AI is the new electricity,” he writes, especially in sectors like retail.
“Greater computing power and real-time contextual processing will make AI instantaneous and seamless in customer and business situations,” he adds. Sensors and IoT are digitising physical stores, and products will talk to supply chains, customers, and personal consumer bots.
“Taste, smell, texture, feel – all are open to customisation,” Atul writes. In the smarter store, in stock becomes in network. “The magic about being a technologist today is that you are also a storyteller,” he enthuses.
Prithvijit Roy, Founder of BRIDGEi2i Analytics Solutions, tracks tech transformations in the consumer packaged goods industry. Companies in this sector face challenges such as the competition between Amazon and Walmart, which is driving prices lower.
AI is being used to decode customer sentiments, create intelligent product finders (L’Oreal), analyse interviews (Unilever), and monitor facial expressions in stores (P&G). Future developments to watch could be brand try-outs and automatic alerts for replenishment.
Divesh Singla, of PAREXEL, tracks health sector trends such as rise in elderly population, chronic diseases, drug and treatment costs, and government regulations. Application of real world data (RWD) can enhance clinical trial productivity. AI can help understand diseases and patient responses. GPS-embedded asthma inhalers can track when medication is taken.
San Francisco startup Mendel.ai uses AI to match cancer patients to clinical trials. “AI-powered drug discovery is poised to increase,” Divesh writes. IoT helps track shipments across pharma cold chains. Aktana is using ML to optimise messaging to customers across channels.
“Behavioral economics techniques could be used to analyse and reinforce healthy behaviour, while AI can track, measure and recommend ideas,” suggests Sameer Dhanrajani of Fractal Analytics. This can lead to proactive health management.
Mahesh Calavai, of TVS, traces the history of personal and public transportation. For example, World War I accelerated motorcycle production, passenger trains started in 1824, the London Underground emerged in 1863, Daimler Victoria became the first taxi in 1891, and the first gas filling station was in Germany in 1888.
Developments to watch today are connected vehicles and electric vehicles, eg. electric trucklines (Newton in Ireland), electric garbage trucks (Courbevoie in France), underground mining trucks (PapaBravo in Canada), electric cargo ships (China). Advanced Driver Assist Systems (ADAS) improve driver and road safety. Tests of air-taxi drones have already begun (Volocopter in Dubai).
Digital is no longer just a channel extension but a core driver for platform innovation in the travel and hospitality sector, according to Vijaya Kumar Ivaturi, Co-founder and CTO of Crayon Data. He is also the author of The Manual for Indian Startups (see my book review here).
Trends to watch are the shift from asset-centric to traveler-centric and service-heavy models, globalisation, the rise of Asia, and integration of new tech stacks involving biometrics, chatbots and IoT. In the “age of experimentation,” companies will need to adopt an “adventure mindset” to create seamless experiences for travelers.
Travelers can be segmented into simplicity searchers, cultural purists, social capital seekers, reward hunters, obligation meters, and ethical travelers. Innovation is emerging across all phases of the journey: inspiration, booking, preparation, airport operations, in-flight services, arrival, destination, and post-trip experiences.
Arnab Chakraborty, of Accenture Digital, explains that telcos are struggling to match the customer expectation standards set by the likes of Netflix and Amazon. New technologies are moving from the experimental to exponential phases. “Customer loyalty in the digital age is the art of NOW,” he explains.
Machine learning (ML) can help networks become self-aware, self-organising, self-optimising and even self-healing. Telcos need to retain trust while also providing new services for telematics, agriculture and insurance.
RPA is redefining the job market, and will need to factored into corporate growth strategies and “augmented” workplaces, according to Neeti Mehta Shukla of Automation Anywhere. In some areas, RPA is out-performing humans by reducing errors and performing complicated data verifications faster.
New opportunities are opening up for startups in these spaces and sectors. Incumbents can increase their innovative edge via a combination of build, borrow or buy strategies. Alliance partnerships and open innovation will be needed for long-term success.
In the long run, companies need to have a focus on AI governance, legal compliance, and ethics, according to Saraswati Ramachandra of Danske IT. This includes dimensions of fairness, accountability, auditability, reversibility, transparency, explainability, accuracy, security, and even right to be forgotten.
Companies need to set up a data governance office in this regard, as well as an ethics committee. Risks can arise from not checking continuously for unintentional bias in data and algorithms, lack of escalation mechanisms involving human intervention, and not factoring in employee resistance or even sabotage.
To prepare the workforce for the future, alliances are needed between industry, academia and publishers, according to Vikas Gupta, MD, Wiley India. “Learning and innovation go hand in hand, and innovation comes from those who have a sense of wonder, who ask the right questions, and those who do not stop learning,” he writes.
Skills needed even more are problem-solving, critical thinking, user-centric design, and collaboration. A mindset of agility, ability to communicate effectively, and multi-faceted skills are also called for. Tech skills now have lifecycles of just a few years instead of a few decades. Personalised and peer learning activities are useful in this regard, along with projects and hackathons. The research mindset also needs to be reinforced.
Looking ahead, trends to watch are the move from artificial narrow intelligence to artificial general intelligence and artificial super intelligence, according to Pankaj Raj of Wells Fargo. Customers are also becoming active co-creators, and will take on an important role in design.
There are geographical factors at work in this domain, such as the rise of the FAANG and Silicon Valley in the US, BAT giants in China, GDPR in Europe, and India Stack in India. The US will continue to lead in taking large moonshots. Population growth, ageing rates, and economic opportunities will also shape the overall attitudes towards AI in these regions.
“Going forward, we have the potential to create the next miracle by harnessing the collective intelligence of all of humanity supplemented by AI,” Pankaj sums up evocatively.