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Q&A: Thomson Reuters Canada’s Dr. Khalid Al-Kofahi on applying AI to business challenges

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Artificial intelligence is impacting on a range of businesses and professions, moving from something niche to an activity that is part and parcel of everyday operations. Dr. Khalid Al-Kofahi, of Thomson Reuters, provides some insights.

Dr. Khalid Al-Kofahi is a leading artificial intelligence expert and the Vice President of Research and Development at Thomson Reuters Canada. Dr. Al-Kofahi heads up the company’s corporate R&D work globally and he leads its Toronto-based Centre for AI and Cognitive Computing.

Dr. Al-Kofahi has expertise in applying AI to help Thomson Reuters’ global customers unearth key information that help to solve their business challenges. Al-Kofahi has developed AI algorithms that have transformed the way professionals carry out their jobs.

To understand how AI is reshaping businesses activities, DX Journal caught up by Dr. Khalid Al-Kofahi.

Digital Journal: How important is artificial intelligence becoming for business?

Khalid Al-Kofahi: I don’t look at Artificial Intelligence (AI) and Machine Learning (ML) in terms of a degree of importance – they are. I think of them as critical for medium and large businesses, regardless of their sectors.

AI and ML technologies are either necessary to optimize how businesses create and deliver value to their customers or part of the value proposition itself. In my opinion, businesses with a large digital footprint fall into the second category.

For example, in the information industry AI is necessary for content aggregation, enhancement, organization and delivery – at scale. AI-enabled applications deliver content, data and insights to knowledge workers within the context of their tasks and often personalized to customers’ preferences.

And the figures speak for themselves: McKinsey & Company expects global economic impact of AI to be between USD $7.1 trillion to $13.1 trillion by 2025. In Canada, AI is expected to add an additional CAD $636.1 billion to the economy by 2035, according to Accenture.

DJ: Which types of sectors are set to see the greatest AI growth?

Al-Kofahi: The obvious ones are healthcare, education and transportation. Beyond that and in industries closer to my lines of business, the financial sector has been an early adopter of AI technology and I expect the growth trend to continue, if not accelerate. The tax and accounting industry will see the biggest disruption.

Not necessarily at the job level, but at the task level (e.g., within audits). Businesses – across sectors – operate in increasingly more complex regulatory environments, thus driving demand for AI-enabled applications to help them understand and comply with relevant rules and regulations. This, for example, was the driver for our most recent product, Data Privacy Advisor, which we developed jointly with IBM Watson to help data privacy professionals stay on top of those ever-changing regulations, keeping their organizations compliant.

DJ: What types of things can businesses do with data analytics?

Al-Kofahi: Every organization accumulates data and the trick is understanding how it can be leveraged for business advantage. The right data analysis can unlock business critical insights such as customer buying habits or even anticipating a fault in your machinery before the error even occurs, preventing costly repairs and downtime.

For example: let’s say a Toronto-based retailer wants to open an outlet in Calgary. By gathering information from existing customers – including preferences, age ranges, socio-economic groups and spending habits – the company can run an analysis and create a general profile of those most likely to purchase at their retail shop. These profiles can be compared and analyzed against demographics in Calgary to pinpoint locations where there is a high concentration of likely customers. Ultimately, leveraging data this way helps to inform a company expansion plan.

DJ: What advantages does AI hold for the legal sector?

Al-Kofahi: The legal industry – despite its rather conservative business model – has been one of the biggest beneficiaries of AI technologies (relative to its size) and it will continue to provide fertile ground for AI scientists and engineers to have an impact. Did you know that the first commercially available search engine that deploys probabilistic rank retrieval was developed in the legal sector back in 1993? I have been developing AI and ML enabled applications for the industry since 1995 and found the sector to be extremely rich ground for AI.

The reason law is so interesting to AI researchers is that it touches upon all aspects of personal and business worlds. You have rules and regulations that govern acts and transactions. Some of these rules have been codified, others are still subject to a significant degree of interpretations. This challenge makes it interesting to natural language processing and knowledge engineering and reasoning.

Attorneys and judges often think by analogy, applying the same legal principle to many factual situations. This makes legal research a particularly interesting and challenging problem. But the rules (law) change over time through legislation and supersession and the technology needs to adapt accordingly. The adversarial nature of the law raises sentiment and polarity to a whole new level. The language you find in case law can be about childcare, medical malpractice, contracts, personal finance, tax obligations, which makes this one of the most interesting problems for NLP researchers.

These are just some examples of where AI and ML are already having a significant impact on the practice of law. Other opportunities include those focusing on reducing the cost and complexity of the law – including online dispute resolution systems, contract review, eDiscover and so on.

DJ: How about a different field, like journalism?

Al-Kofahi: AI can deliver huge advantages to journalists and we’re already seeing the results in our company’s own news division. Over the last 165 years, Reuters earned a reputation for gathering quality information, producing news free of bias and getting it to readers the fastest. Those pillars are still very much a part of how the news division reports on events now. But in a connected and fast-moving world, the challenge of capturing and reporting on news at scale takes on a whole new meaning.

To address this challenge, we developed Reuters News Tracer – an AI powered platform that can capture events as they are reported around the world, filter out the noise (e.g., chat, spam), identify reporting of news worthy events, distinguish between reporting of ‘facts’ and opinions and then algorithmically assess the veracity of this reporting. Our journalists have been using this system, which allows them to consistently, and accurately, report on events well before any other news outlets publish their own accounts. In fact, over the last year Reuters has been first in more than 50 major news stories thanks to Tracer.

DJ: Does the promise of AI sometimes disappoint?

Al-Kofahi: Yes, of course. Sometimes disappointment is caused by hype and people and organizations talking about the future – even the distant future – in the present tense. Other times, it is due to lack of understanding of inherent biases of AI algorithms especially in task-critical applications. And other times because the technology may still need additional vetting and testing.

I am not sure if this falls under this category, but the race to build the first autonomous vehicle hinges on AI and it certainly feels like we are on the cusp of a breakthrough; however, there is still risk to human life. The reality is that developments will be incremental before that safety benchmark is fully achieved. This might seem slower than the pace of some other technological developments, but the outcomes will be worth the wait.

DJ: Please explain about your work with the Toronto-based Centre for AI and Cognitive Computing

Al-Kofahi: Thomson Reuters has been applying AI technologies in products for more than 25 years. The Toronto-based centre is part of our larger R&D team which I also lead. Together, our objective is to simplify and transform knowledge work, focusing on opportunities that could be enabled by AI and machine learning.

This includes how we collect, enhance and organize content. How we deliver this content to our customers (e.g., search, recommender systems and navigation) as well as a diverse set of vertical products and capabilities that addresses specific customer challenges (for example, the Data Privacy Advisor or Reuters News Tracer). Personally, I have been focusing on attracting top talent, establishing the right culture and operating rhythm and supporting the team to ensure they are able to utilize their skills to create value for our customers and our business.

DJ: Who is the Centre aimed at?

Al-Kofahi: Our customers are across the legal, financial and risk, tax and accounting and media sectors. We aim to develop ‘smart’ applications that delight our customers. These are applications that are responsive (to their input), that are task focused and customer aware; applications that are robust, proactive (when appropriate) and offer an intuitive experience. This requires us to develop advanced AI and ML capabilities ‘under the hood’, which means we must continue attracting and retaining the very best talent in the industry – and why this particular centre is based right here in Toronto.

DJ: What are the key projects that the Centre is working on?

Al-Kofahi: The best example of our most recent work was the launch of Data Privacy Advisor. But, let me assure you there is more to come. I’d be happy to come back and elaborate on some of these projects after we launch them.

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#ScaleStrategy Q&A: Managing the Growth Bandwidth

Tech veteran Dean Hopkins on what it takes to scaleup — and down — in both startups and enterprise organizations

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Dean Hopkins, Chief Growth Officer at OneEleven. - Photo by DX Journal
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#ScaleStrategy is produced by DX Journal and OneEleven. This editorial series delivers insights, advice, and practical recommendations to innovative and disruptive entrepreneurs and intrapreneurs. Read the first part of the interview with Dean Hopkins here. 

While working at McKinsey in the 1990s, tech veteran Dean Hopkins first stepped into the world of the internet.

“This was 1993. No internet existed as we know it,” says Hopkins, now the Chief Growth Officer at OneEleven, recalling how he discovered the work of Marc Andreessen. “At that point in time, he was demonstrating his early browser concept and talking about how the future of the internet was going to be huge. I caught the bug and decided I would leave McKinsey and start my first company called Cyberplex.”

After a bit of a bumpy start, Cyberplex scaled quickly. “Cyberplex tripled every year and grew to 500 people with $50 million in revenue and $975 million market cap,” he says.

Then 2001 hit. “That was the peak of the cycle followed by a trough. It was the biggest learning experience of my career. I had to descale the company to survive,” he says. Over seven quarters, Hopkins took the team from 500 to 50 and brought the company back to profitability. He then  transitioned Cyberplex to new leadership and moved on to his next challenge.

For the next 12 years, Hopkins worked as a management consultant with his own boutique firm that was focused on driving global transformation initiatives for companies such as Thomson Reuters and the Ontario Teachers’ Pension Plan Board.

With both entrepreneurial and intrapreneurial expertise, Hopkins is now applying his global growth skills to transform OneEleven’s unique scaleup model into a worldwide Scale-as-a-Service model.

Read what Hopkins has in store for OneEleven’s global growth.

We recently spoke to Hopkins about tough lessons he learned at  Cyberplex, how enterprise growth is different than startup growth, and how he’s applying these lessons to expanding the OneEleven model globally.

DX Journal: When you think back to your time when Cyberplex hit its inflection point, what did you learn about scaling?

Dean Hopkins: Culture and people were the two things that allowed us to handle both the steep trajectory both up and down. Those things got us through the crazy knee in the curve and probably more importantly, helped us when we needed to descale.

Attracting amazing people that became my partners in growth was the reason we were able to scale. I couldn’t have done it alone.

Secondly, we built a culture that was accustomed to scaling and had an appetite for growth. Our culture was about resilience, and scaling, and picking yourself up and dusting yourself off. We made it okay to make mistakes, then march on.

DX Journal: Why people and culture? Why isn’t it all of the other things?

Hopkins: It’s a great question. In a culture where the decision-making takes a long, protracted time, where risk-taking isn’t there, and where people have to analyze things to death before they can make a decision, scaling is impossible. People would crumble under the weight of scale because the number of things coming at them.

To scale, it’s important to trust that people are all working toward the same goals and are empowered to make decisions.

That’s where culture comes in. It becomes a culture that can tolerate the bandwidth of needs that come with growth. If I didn’t have both of those things — good people ready to make decisions and a culture where I allow them to do it — I would have failed to scale.

The other things like technology, offices, infrastructure, are secondary when you distill it down. Companies that are successful across different geographies, industries, offices, become that way through empowering their people and building a culture that tolerates growth.

DX Journal: When you moved out of Cyberplex and into Thomson Reuters and you were managing a large-scale transformation. How did you manage scale within an environment as big and complex as Thomson Reuters?

Hopkins: The first thing I noticed was pace slowed down dramatically. What used to take me a week or a month now took 6 to 8 or 12 months. Large organizations only have the capacity for so much change. Once I did get the ship to turn in a new direction, I moved a lot of people, revenue, cost, and dollars. I had to be patient enough to let it take hold. The experience was much more of a marathon where I had to think multiple chess moves ahead and let the game play out.

DX Journal: How do you know when to modify your approach or give up when dealing with  transformation in a large organization?

Hopkins: I didn’t do a great job of it at the beginning. I pushed an entrepreneurial agenda at an entrepreneurial pace, and very quickly ran headlong into blockers. I had to adapt and use an experimentation model. I tried different levels of throttle until I got to a point where the organization was willing to accept it. I learned to read the frustration on peoples’ faces saying “okay, no more, Dean. I can’t take any more of this” and built relationships with people where they were able to tell me that.

I was able to adapt and adjust my own style to better reflect the environment. Then over 12 years, I gradually increased the tolerance for risk-taking and for change within the organization. I would work with specific people to help them increase their ability to drive change. What was first gear early on, became second and third gear closer to the end of my tenure. Ultimately, the organization became much more comfortable with making change at a higher rate.

DX Journal: What’s a scale lesson you learned the hard way?

Hopkins: I learned to hire slowly and fire quickly based on fit. One rotten apple really can spoil the bunch. As part of this, I learned to listen very closely to my people. The people on my team knew about someone that didn’t fit long before I did. By listening, and taking quick action, I saw the immediate positive impact on culture.

Finally, I learned the value of getting out of the way. By fully trusting people, providing them good direction and support when needed, it activates them to reach their full potential. All of these were learned through many failed attempts, and I have the scar tissue to prove it.

DX Journal: What signals do you use to know you’re on the right path when you start to scale something and you’re trying to measure if it’s working?

Hopkins: One of the reasons we were able to survive at Cyberplex — both the growth and the decline — is that we had very good leading indicators of the business. We had invested heavily to try and understand what our funnel looked like, what our planned capacity was, and we had the metrics dialed in. Every month and every quarter, we constantly refined our ratios so we had a really good sense of what was coming. When things started falling off the cliff, we trusted our instruments and started acting accordingly.

Read more about Dean Hopkin’s plans for expanding OneEleven globally.

 

DX Journal covers the impact of digital transformation (DX) initiatives worldwide across multiple industries.

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#ScaleStrategy Q&A: OneEleven’s Chief Growth Officer on Building a Global Scaleup Knowledge Base

Dean Hopkins’ is aiming to build and deploy a Scale-as-a-Service model worldwide

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Dean Hopkins, Chief Growth Officer at OneEleven. - Photo by DX Journal
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#ScaleStrategy is produced by DX Journal and OneEleven. This editorial series delivers insights, advice, and practical recommendations to innovative and disruptive entrepreneurs and intrapreneurs. Read the second part of the interview with Dean Hopkins here. 

“We’re being ambitious. We want to show scaling companies that we can scale, too,” said OneEleven’s Chief Growth Officer, Dean Hopkins, when the Toronto-based scaleup hub announced its plans to expand to Ottawa, Vancouver, London and Berlin in late 2018 and into 2019.

It’s an opportune time to expand globally as a scaleup hub.

According to CB Insights, total annual venture capital global funding “increased nearly 50% in 2017, as over $164B was invested across 11,042 deals. Deal activity was up by 11%, with both deal and dollar figures representing annual highs.”

As for 2018 so far, KPMG’s Venture Pulse Report says “for the fourth consecutive quarter, VC invested has exceeded $45 billion, and in the most recent quarter, just barely fallen shy of $50 billion once more.”

Hopkins is excited to walk the scaleup talk once again.

A tech scene veteran, Hopkins was the CEO & Co-founder of Cyberplex for more than a decade where he grew the organization from a startup to a public company with nearly $1 billion in market capitalization. During his career at Cyberplex, he also successfully managed the company through a major downsizing as the tech bubble collapsed and transitioned it to new leadership where the company enjoyed another round of growth.

Prior to joining OneEleven as Chief Growth Officer, Hopkins ran a boutique management consulting firm he founded in 2006 to drive transformation initiatives on a global basis for clients such as Thomson Reuters and the Ontario Teachers’ Pension Plan Board.

We caught up with Hopkins to talk about scaling lessons, OneEleven’s growth plans and developing the world’s leading source of scaleup knowledge.

DX Journal: You have extensive experience scaling from both an entrepreneurial and intrapreneurial perspective. What are some of the lessons you’ve learned?

Dean Hopkins: First off, it’s all about people. Attracting amazing people that became my partners in growth was the reason we were able to scale. I couldn’t have done it alone. ‘Hire great people and get out of their way’ became my mantra — even to this day.

The second ingredient to scale was culture. We had built a culture that was accustomed to scaling and had an appetite for growth. Our culture was about resilience, and scaling, and picking yourself up and dusting yourself off. We made it okay to make mistakes, then march on.

Read our interview with Dean Hopkins on his scaleup experience at Cyberplex and his transformational work in Thomson Reuters.

DX Journal: What have you learned about scaling at OneEleven?

Hopkins: Early on after I joined OneEleven, I sat in on a community lunch with about 300 people from all the member companies. At this lunch, new members are brought up in front of the crowd to say a little about their company. Then 300 people welcome them with cheers — a lot of love goes their way. After that, others come up to talk about their big wins, like raising money, landing a big customer or completing a big launch. And again, 300 people applaud and celebrate them. Well, I remember sitting there thinking, ‘where was this when I was building Cyberplex?’ I was in a hovel by myself toiling away with no community other than people that I would lean on as advisors. I never had the kind of kudos, support, warmth, love, resources that these companies have at OneEleven, and that’s when things clicked for me. This is what community is. A lot of people talk about community, but to actually see it viscerally done, made me realize I needed to recreate it in other geographies.

What we’re trying to do is get a group of companies — all individually pursuing their dreams, but collectively working together — to make sure that each other are successful.

DX Journal: You’re focused taking this OneEleven scaleup initiative global. How do you assess where you need to be?

Hopkins: A big aha moment for me around OneEleven was getting the Startup Genome report. I looked at our success in Toronto and yet our city was number 14 or 15 on their list. I said, ‘wait a minute, OneEleven is working incredibly well in the 15th best market?! What if we took OneEleven and built it out to some of the top 10 markets? That’s what led to the business plan we’re currently executing.

From there, I overlaid our partner Oxford Properties into the mix. As a large global real estate firm, this gave me the first 4 markets to go after — London, Berlin, Boston, Vancouver. We’re studying each market, mapping the ecosystem, understanding who the players are, comparing it to Toronto, figuring out what the differences and similarities are and then plotting our entry. Over the next year, we’ll be in each of those markets.

The approach to entering each of these markets will be subtly different depending on character of the market. We’ve invested a lot in meeting the community, understanding who does what to whom and how we can add value. By the time we launch in those markets, we’ll already have a reputation built up because we’ll have spent some money to support the local ecosystem. We’ll have brought some value to some of the companies there by helping them maybe come to Canada or come to one of our other markets. I view it as kind of putting some karma in the bank before we even launch in each.

DX Journal: When OneEleven enters a geography, what’s the benefit to companies and communities located there?

Hopkins: From our perspective, there are 3 key benefits to having OneEleven in your city.

The first is that we’re building the global knowledge base of scale. Each community we add is bringing a new rich set of perspectives on how to scaleup businesses. We then make that available to everybody in the peer community.

The second benefit is for the companies in each geography is an easier path into other markets through our growing global ecosystem. If a company in Toronto wants to go to London, they can access continental Europe because we have assets and relationships in Berlin.

Lastly, we are building what we call Scale-as-a-Service. This is a set of capabilities — much like you’d find on Amazon but only dedicated to scaling — that help people with the common challenges of scaling. This only gets richer and more pressure-tested the more markets we serve. We’ll have the best set of Scale-as-a-Service capabilities of anybody out there because we’re activating across companies in multiple markets.

DX Journal: Speaking of a scaleup knowledge base, as a company grows are there one or two things that really become important?

Hopkins: Entrepreneurs 100% need to think about getting away from the technical, engineering-focused orientation of their early stages. They should focus their time disproportionately on building their channel to market, building their go-to market, building their customer base, building their way in which revenue is going to come to them. Build protected paths to market that are defendable, because that’s really where the source of competitive advantage is. An entrepreneur could have the best product in the world, but if he or she can’t get it to market the company is dead. The companies that figure out how to build proprietary go-to market or protected go-to market are the ones that end up winning.

The second thing is not to underestimate the complexity of the people equation. Most founders who have reached the scaleup phase realize they need to think about organizational design, career paths for employees and what the organization will look like in 3 years. If they don’t, they will have a churn problem, which is very expensive and disruptive for the business.

The third thing is preparing for the next big round of funding. Generally speaking, people underestimate the amount of relationship building and preparation work needed. It probably takes a year or so to get ready properly. We’re trying to help companies diagnose where they are, how much runway they need and prepare them adequately for the big round, which is another league up from what they’re normally used to.

DX Journal: What books have you read that helped you get through your scaleup journey?

Hopkins: I love Jim Collins. Anybody who hasn’t read Built to Last, shame on you! [Laughs] You need to read it and Good to Great.

I’m also a big believer in a book called The Alchemist by Paulo Coelho. It’s all about finding personal motivation and that gets you through some very challenging times when you’re leading a company. There’s a book called The Speed of Trust by Steven Covey, which is all about how to engineer trust in your organization, which is essential at this level. Lastly, Crossing the Chasm by Geoffrey A. Moore. A seminal work on how you market and build a go-to market strategy.

DX Journal covers the impact of digital transformation (DX) initiatives worldwide across multiple industries.

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Businesses should ‘follow the money’ when adopting AI

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A June report from the McKinsey Global Institute (MGI) found that, overall, artificial intelligence adoption is still slow; only 20 per cent of “AI-aware” businesses say they are adopters.

The MGI report on AI discussed the difference in AI investment and adoption, with investment in AI technologies experiencing a threefold external investment growth since 2013. Compared to that figure, 41 per cent of firms told MGI that they are uncertain about the benefits, and within that 20 per cent of adopters, 10 per cent are adopters of three or more AI-backed technologies.

new report from Harvard Business Review on the two major business potentials of AI said that while this may be the trend on average, “senior executives know that AI isn’t just hype.”

HBR attributes some of the hesitancy to adoption to business leaders not being sure where they should be applying AI, and after McKinsey researchers Michael Chui, Nicolaus Henke and Mehdi Miremadi took a closer look at 400 AI use cases from 19 different industries, and nine business functions, they found that the question of where to put AI to work in a business is a matter of playing “follow the money.”

“The business areas that traditionally provide the most value to companies tend to be the areas where AI can have the biggest impact,” the report explains.

The two areas that HBR found to the implementation of AI to have the biggest impact are: supply-chain management/manufacturing and marketing and sales.

Chui, Henke and Miremad also found that another way for businesses to find an area to introduce AI is “to simply look at the functions that are already taking advantage of traditional analytics techniques.” Meaning that business leaders should look to apply AI to parts of the company where neural network techniques could provide a higher performance, or “generate additional insights and applications.”

According to the MGI report, companies that have a low AI adoption rate are in the education, health care, and travel/ tourism sectors.

In a previous Digital Journal article on how hospitality brands can undergo digital transformation, it was stressed that “hospitality brands can use new technologies to make their businesses hyper guest-focused.” Utilizing AI for marketing and sales purposes is just one way of making that happen.

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