Follow Us











Startup Sectors

Women in tech







Art & Culture

Travel & Leisure

Curtain Raiser

Wine and Food



An eye on AI – CII Global Knowledge Summit explores impacts and strategies for the Age of the Algorithm

In our third preview article on CII’s upcoming annual summit, we share insights on AI frameworks, impacts, and ethics.

An eye on AI – CII Global Knowledge Summit explores impacts and strategies for the Age of the Algorithm

Thursday June 25, 2020 , 13 min Read

Next month, CII’s annual summit will explore the digital transformation of knowledge societies. To be held entirely online from July 6-8, the forum is titled CII Global Knowledge Virtual Summit 2020: Knowledge in the Age of Artificial Intelligence.

The lineup includes speakers from Standard Chartered Bank, Wells Fargo, Bosch India, Mindtree, Trianz, CGI, Wipro, Infosys, TCS, AIQRATE, AFCONS Infrastructure, L&T, Xenvis Solutions, NISG, MyGov, and Government of Karnataka.

The conference is also supported by the KM Global Network (KMGN), and will feature the awards ceremony for the Most Innovative Knowledge Enterprise (MIKE). AFCONS, Infosys, Wipro, Cognizant, and Tata Chemicals are winners of the MIKE Awards at the India and global levels.

YourStory is the media partner for the summit this year as well (see Part I and Part II of our 2019 summit articles). Topics addressed this year include the rise of AI/ML, knowledge integration, gamification, and storytelling.

In this series of preview articles, YourStory presents insights from the speakers and organisers of the CII 2020 summit, as well as experts from KMGN (see Part I and Part II of our ongoing coverage of the 2020 edition). The knowledge movement has particular urgency in the wake of COVID-19 to speed up effective knowledge-sharing across sectoral and national boundaries.

Artificial intelligence: impacts

In a chat with YourStory, Jennifer Mecherippady, Senior Vice-President of CGI, shows a number of AI benefits that have been realised by her company. These include digital transformation of AM/IM (application/infrastructure management) operations through its Intelligent Automation Platform, responding to RFPs based on insights from specifications and past data, and digitisation of industry-specific needs in banking and HR.

A number of case studies of AI have shown broader impacts across industries, explains Sameer Dhanrajani, CEO of AIQRATE. He is also the author of AI and Analytics: Accelerating Business Decisions (see my book review here).

The case studies cover AI impacts in media (innovative content creation via hyper-personalisation and micro-segmenting), insurance (transformation of the business value chain in claims processing, telematics, risk management, actuarial valuations), and manufacturing (predictive asset maintenance to pre-empt wear and tear).

Other examples cited by Sameer are in healthcare (deep learning algorithms to analyse millions of X-Rays, CT scans, MRIs) and factory management (real-time insights for intelligence generation and decision-making).


“We are being ushered into an AI era, an algorithm-led economy wherein self-intuitive and ML- enabled algorithms sit at the core of every business model and in the organisational DNA, delivering end-to-end transformative impact,” he explains.


“Machines are great at evaluating huge volumes of data and generating clever visualisations from these. AI is also good at finding trends that humans can’t immediately see due to the volume of data and possible interfering counter patterns,” explains Arthur Shelley, Founder of Intelligent Answers.

A number of other experts have documented specific impacts of AI and ML in companies like Amazon, GE, Bosch, Nike, Caterpillar, Spotify, Netflix, SAP, Cisco, IBM, Siemens, Verizon, Unilever, P&G, GSK, Novartis,, DBS Bank, RioTinto, Lowe’s, AllState, and AlphaGo. See my book reviews of Prediction Machines; What to do when Machines do Everything; Machine, Platform, Crowd; The AI Advantage; and Human + Machine.


Synergy: artificial intelligence and knowledge management

“Every five years or so, the field of KM undergoes a metamorphosis, absorbing the latest trends into its practices and thereby delivering continuing value,” explains Rudolph D'souza, Chair of KMGN and Chief Knowledge Officer of AFCONS Infrastructure. He cites the rise of the internet, social media, and enterprise digital platforms as examples of such waves.

“The same is going to happen with AI, automation, and machines. What will change is the pace, the sources of knowledge, and in this new era – the application of knowledge,” Rudolph says. The role of KM is to absorb the latest applications to serve organisation needs to compete effectively.

“We will see the application of knowledge increasingly getting decided by ‘self-learning algorithms,’ a term I have coined to include bots, whether software, hardware, or a combination of both,” he adds.

This is already happening, mainly in the form of simple decision support where the implications are not catastrophic. “But some use cases of higher-end applications have been around, as in the case of using machines to analyse scans in oncology departments and ‘assist’ specialists,” Rudolph observes.

“Knowledge creation and management is a critical differentiator for the industry. With AI making great strides in generating knowledge from raw video, image, voice, and social media text, knowledge creation and management has to be redefined,” explains Gopichand Katragadda, Chairman, Global Knowledge Summit 2020, and Founder and CEO at Myelin Foundry.

“Artificial Intelligence is also critical in times of significant change in industry and society being driven by the pandemic,” he adds. Hence the core theme of this year’s CII summit is Knowledge in the Era of AI.

The rise of AI and automation will lead to the increasing embedding of relevant knowledge about decisions, design, and processes right into the code, according to Ravi Shankar Ivaturi, Business Operations Senior Director, Products and Platforms, Unisys. This can lead to positive and negative effects, he cautions.

Structured KM lays the foundation on which AI, machine learning, and automation can thrive, according to Ved Prakash, Chief Knowledge Officer of Trianz. “The role of KM is only going to increase in the emerging scenarios where deep understanding of knowledge and data will be a key skill,” he adds.

“The role of KM is going to be that of a connective tissue across systems, machines, and humans. The game is still about insights,” explains Balaji Iyer, Director of Knowledge Management and Enterprise Transformation at Grant Thornton.

“Many processes are automated in a ‘HUMBOT’ framework where humans work closely with bots to get the desired outcomes. There is a crucial knowledge play in areas of machine teaching, human-bot hand-offs, and solving the right problems,” he adds

“The more AI makes a lot of the processes appear like ‘black boxes’ for business leaders, the more pronounced the need for a next-gen KM program,” Balaji says. He also draws attention to the re-imagination of KM systems using AI as a backbone for an AI-driven world, with KM products like Microsoft’s Cortex as an example.

“AI will continue to be used to replicate human cognitive functions such as memory, learning, evaluation, decision making, and problem solving,” says Zeba Khan, Managing Partner, Xenvis Solutions. “The role of the human factor in aspects of creativity, intuition and in other soft skills cannot be replaced by technology. AI will not replace human jobs but will redefine them,” she emphasises.

“AI needs knowledge to properly operate and produce valuable results. KM will help producing the raw material for AI and support the AI process at every stage,” explains Vincent Ribière, Managing Director and Co-founder of the Institute for Knowledge and Innovation Southeast Asia (IKI-SEA), hosted by Bangkok University.


“Every organisation using AI aims to have knowledge embedded into a system to perform the roles humans do at lightning speed,” observes Rajesh Dhillon, President, Knowledge Management Society (KMS), Singapore. Knowledge sharing, collaboration, reuse and learning are the impetus for implementing KM and keeping AI relevant.

“AI-assisted collaboration tools can take knowledge management to another level,” observes Refiloe Mabaso, Deputy Chairperson of Knowledge Management South Africa (KMSA). AI and KM combined can help teams and organisations operate even more intelligently.


The human factor in AI and KM

“What AI is not (yet) great at is finding the gaps or creatively connecting the insights that may be possible. The future is about what is possible in future and this is informed from what currently is and can’t be done,” explains Arthur Shelley of Intelligent Answers.

“This is where collaboration between AI and human creativity offers more than either alone can achieve,” he adds. Based in Melbourne, Arthur is the producer of the ‘Creative Melbourne’ conference, and author of KNOWledge SUCCESSion, Being a Successful Knowledge Leader, and The Organizational Zoo.

“Applying human creativity to the visual analysis of the increasing volume of data is where the magic ideas for the future will form, connect, be assessed, and eventually create our future possibilities,” Arthur advises.


“AI and automation can be beneficial, but humane and responsible automation is important for balancing the unemployment and cost,” cautions Sudip Mazumder, Head of Engineering and Construction, Digital at L&T NxT, and General Manager, L&T Group. “AI may lead to ‘dehumanised’ processes as people’s behavioural drivers may not be mapped in an AI model,” he explains.


“There will be realignment of the human-machine equation in the context of AI proliferation in the Industry 4.0 era,” explains Sameer Dhanrajani of AIQRATE. “However, akin to all three previous revolutions, AI progress will redefine jobs and human roles a few notches up,” he adds.

He foresees a change in workforce composition with menial and trivial jobs getting redefined with AI and redesigned with human-machine combinations. “However, platform aggregators and the gig economy will open up new work opportunities for the workforce.

“A new potent combination of humans and machines will lead to increased efficiencies and effectiveness scenarios in the enterprise,” Sameer predicts.


“A world that was hurtling at a relentless pace towards automation, AI, and ML has been forced to stop in its tracks and take cognizance of the human in the process. And, it took a virus to do that,” cautions Rajib Chowdhury, Founder of The Gamification Company.

Working from home is ineffective without emotional trust, a sense of ownership, self-motivation, and measures of accountability, he adds. “Let us not forget that we humans are fundamentally social beings. Technology is but a medium that plays a role of enabler to the process,” he emphasises.

The human factor is still key in a world of AI, explains Jennifer Mecherippady of CGI. This includes identifying potential problems and measurable metrics, providing the right data sets, attributes, and values, and finally evaluating the business outcomes.

Ethics and AI

“The screaming need for KM in the age of automation, ML, and AI is to formulate and implement frameworks for the Governance of Human and Machine Knowledge,” emphasises Arthur Murray, CEO of Applied Knowledge Sciences, in Washington DC.

“Knowledge, whether human or automated, does not manage itself. It requires, as we like to say, ‘adult supervision,’” he explains. In a recent column, he shows how these challenges manifested themselves in Microsoft’s aborted Twitter chatbot Tay.

Arthur urges automation-intensive organisations to keep checking on the validity of their algorithms, and put in place a knowledge-governance board, which scopes out which domains to explore or avoid.

KM practitioners should strategically work with executive management to measure and update performance impacts of AI, advises Moria Levy, CEO, ROM Knowledgeware. They should examine how AI can, or cannot, support critical decisions. This involves knowledge validation, sense-making, and risk analysis.

A number of experts have weighed in on broader ethical dimensions of AI with respect to embedded bias, monopolistic practices, global governance, and lack of transparency and accountability. See for example my book reviews of A Human's Guide to Machine Intelligence, Life 3.0, The Four, and The Platform Society.  

Myths and misconceptions about AI

Despite the presence of AI for decades, a number of myths and misconceptions persist, and get in the way of harnessing AI. Jennifer Mecherippady of CGI points to some such myths: AI will replace humans and overtake human intelligence, AI can make sense of any data and learn the way humans learn, and AI will give immediate business results.

There is also lots of confusion between traditional automation and intelligent automation, she adds. Another misconception is that businesses needs scientists and huge investments to adopt AI.

Many companies are embracing digital transformation without fully understanding the key role of analytics and AI, cautions Sameer Dhanrajani of AIQRATE. “The road to digital transformation is incomplete without AI being at the fulcrum of the business. Enterprises cannot adopt AI if the foundational aspects of analytics capability are not in place in the journey to AI,” he emphasises.

Lack of awareness of AI impacts gets in the way of evangelising and democratising AI, he adds. AI calls for disrupting the business value chain of the enterprises and replacing it with high powered ML-enabled algorithms.

Organisational development and upskilling for AI

The speakers offer a range of tips for professionals and organisations to upskill themselves for a world of AI. “You need to identify different groups of people and upskill them. For example, programmers need to be able to identify, implement, refine, and manage new models,” Jennifer Mecherippady of CGI explains.

Business users should master how to effectively use intelligent systems for solving new business problems. “Business consultants should be able to understand business problems and identify the right use cases to invest in AI,” she adds. Use case identification, collaboration, and scaling call for a systematic learning process.

“Only eight percent of organisations under an HBR study show core practices that support widespread adoption of AI. A reason for that is a failure to rewire the organisation to be able to collate the AI application-needs coming from internal stakeholders or clients,” Jennifer explains.

“AI therefore should be owned by the teams invested in driving the benefits for customers,” she adds. CGI’s organisational model alignment emphasises a flattened structure consisting of just five level to business unit leaders.

“Learning will not be a one-time effort. It will be a continual one and the market will unleash new exponential technologies, business practices, and disruptive scenarios in rapid time cycles,” observes Sameer Dhanrajani of AIQRATE.

“Innovation and transformation will be the new business realities on a real-time basis. Knowledge professionals will have no option but to look at revisiting their career choices every few years to ensure that they remain relevant,” he advises.

“The basic needs for survival so far have been roti, kapda, makaan, and data. All professions will be forced to add the fifth element – learning – into their monthly budgets to ensure that they remain topical on skills and competencies,” Sameer jokes.

The road ahead: pandemic and beyond

The speakers offer a range of tips for businesses to harness AI. “Continue looking for strong opportunities and business cases for AI. Make it a goal for your teams,” advises Jennifer of CGI.

“Many enterprises have only a short-term measure for AI adoption and focus only on PoCs or limited engagements. Instead, they need to make AI integral to the strategy of the enterprise and a rallying cry,” Sameer of AIQRATE urges.

“The COVID-19 crisis will accelerate AI adoption in totality and across industry segments. Customer preferences have drastically changed, and operational processes have been altered because of this Black Swan event,” Sameer observes.

“AI adoption with its ability to pre-empt scenarios and bolster decision making abilities will be the need of the hour for enterprises to make informed and timely decisions,” he explains.

“However, as the current running algorithms have been fed with historical and episodical instances of the past, the coronavirus crisis will compel enterprises to alter the algorithms with revised assumptions and variables. Otherwise, these pre-configured algorithms may create biases in the existing data sets and provide distorted recommendations to the stakeholders,” Sameer cautions.

“AI is a strategic differentiator for revival and competitive advantage, and a secret sauce for growth and scalability. Let us not use it like a tool or just a technology,” Sameer sums up. This calls for re-imagination the business, strategising the building blocks of AI, and mapping the AI maturity curve.

Edited by Megha Reddy