Playing back 2017, on Christmas day

I started 2017 on a rather sad note, having lost our older fur baby Boss towards the end of last year. A year has passed since the day he went to sleep on my lap and that pain lingers – though I must say old photos of him do make me smile more now.


To their credit, Hobo and Ollie have been trying their best to cheer me up since Boss left us .


On the bright side, I also had started in a new role in IBM as the GM of Cognitive business in North America, which made me excited and nervous in equal measure .


I inherited a team that was 4 times larger than my last one , with an extra zero at the end of my target numbers . Almost every one of my direct reports had managed me at some point in my past career – so I had a group I had known very well and trusted each other for a long time. I had a new manager, whom I knew from before but hadn’t worked with since then (who turned out to be a great friend and mentor) . To make things even more exciting, I also got a portfolio that was a mix of our bread and butter businesses and our hyper growth businesses .

We were not short on opportunities or challenges this year. Giving confidence to clients across North America to pioneer new technology, modernizing our skill sets and business models , integrating new members into our gang and bidding farewell to several friends , learning the parts of the business I did not work on previously, Acting as a sounding board to my team mates , Getting mentored by great leaders … it just was a blast !

I learned a lot too!

One of the biggest learnings for me was that “Authority is an illusion “. I had heard it before but now I have a first hand appreciation of what it means. I had to learn how to influence and motivate more than use formal authority. I am far from mastering it, but I have started on that journey.

I have always prided myself as being good at delegation. And yet it became clear that as scale increases, you have to unlearn and relearn how to lead. And to delegate effectively, I needed to recruit and train better , and learn how to motivate a large heterogeneous team and so on . Clearly I had several areas where I could spend time to improve . And I chose education as my primary theme for the year, while trusting my team to take care of other important aspects of the business .

In retrospect, I am glad I prioritized learning.

We are a services firm which means we are a people business. We are competing in a fast changing market where you become obsolete very fast if you stay still for even a short time. Sponsoring our first business leadership school ( Bee school ) and our Technology school (T school ) also gave me several invaluable benefits I did not expect . I got to meet hundreds of consultants and engineers and learn about their work and what their hopes and fears are . I got a whole new appreciation of several back office functions like Ops, Finance ,HR, L&K and so on than I ever had in the past and as a result I will never take them for granted anymore and will be very grateful for what they do. I met several leaders who volunteered as faculty and learned from their experiences. What an absolute blessing it was !

Some things did deteriorate this year as well . I nearly didn’t read as many books as I usually do . I am getting caught up towards the end of the year, but it’s something I need to keep an eye on for next year.


I also did not blog as much as before – which I am not actually unhappy about . I just switched to more short form posts in LinkedIn . I did have two fleeting moments of internet fame – one for defending Watson and another for highlighting the challenging life of product managers 🙂

2017 turned out to be one of the few years when I didn’t go to India. But my parents and my mom in law visited us here, so at least part of the India visit was covered indirectly .


And I only had one international trip this year , to Japan .

Clearly I was on the road enough to retain my executive platinum in AA and diamond in Hilton Honors with room to spare. Travel continues to be the most unproductive part of this profession that needs an urgent disruption .

One experiment on personal front that I am happy about is on gardening front, thanks mostly to my mom in law staying with us for several months this year .

Between assorted flowers and a small vegetable garden, I started reliving the joys of childhood ! Plenty of rookie mistakes made , but what the heck – it was a lot of fun .

Also, on the (very) positive side – I got to spend more time with my wife and daughter this year than usual. The highlight was the trip to DC and Maine to check out National monuments and fall colors. The big regret on that front was not being able to make Shreya’s concert at school this fall when I was stuck in east coast .

I have practically stopped competing in dog shows, but I was fortunate to visit a few as a spectator and hang out with my old friends and their fur kids. Also for the first time, managed to see the Great Dane Nationals, which happened in Chandler. Icing on the cake was that for the first time since I moved to US, I found 3 friends from India that I showed dogs with back in the day.

All things considered, I am truly grateful for this year. I just wish I spent more time slowing down to smell the roses . Well, there is always the next year to do that, right ?

Wish you all a merry Christmas and a happy 2018 !


Where will AI take us in the short to medium term ?

My guess is as good as yours on how AI will influence the world around us in the long term. All possibilities from solving world hunger to we becoming Cyborgs remain on the table. However, I do have some thoughts on where this field is headed in next few years – say the 5 to 10 year window. As we wind down 2017, I thought I will share four of my thoughts on this topic – enjoy it with your favorite holiday beverage 🙂


Invisible AI vs AI face-offs every second

Several big companies have invested in personal assistants powered by AI – with varying technology maturity. Some of the hottest startups across the world are working on giving the big companies a run for their money. Given I am not an impartial observer given my day job, I will resist the temptation to predict a winner. More and more money and time is being poured into this category across the industry.

Personal assistants will be a part of everything we routinely do going forward. And the change it will bring profound disruption all around us. For example – we might outsource our routine grocery purchases to a personal assistant. The logical next step is for grocers to stop sending us coupons and loyalty cards, and instead market to our personal assistants. That does not need TV advertisements or glossy news paper inserts or targeted emails. That communication is on some machine readable form – say JSON or perhaps even binary. The best Ad agencies will need to hire best AI experts, not (or at least not just) the best creatives.

When customers outsource buying to personal assistants, vendors will need to resort to AI to respond as well. And working backwards, the entire supply chain will need to get redesigned to be a lot smarter. Both consumer and enterprise tech will face a fast faced evolution.


The interesting aspect will be that most of this profound disruption will happen behind the scenes without us realizing what is happening – there will be an AI vs AI face-off (hopefully of a good kind) every second as we go on with our lives blissfully unaware.

AI Safety frameworks will emerge 

As Spiderman said “With great power comes great responsibility”.


This takes many different forms in the field of AI, and might never get fully solved even in long term. Also, vast majority of these smart applications are probably never going to be actually harmful, even though they may become super annoying ( I am looking at you , Linkedin algorithms favoring double spaced god awful posts.) . 

  1. Since fast iteration is the norm for most AI initiatives, it is important that we have some way of proving safety of such applications mathematically before deploying in production. Today, we can already prove somethings – but this needs to improve big time and become mainstream.
  2. We need consistent hardware level protections. Most interactions generating data for AI to work on will be between machines , or between machines and humans. Software cannot be the lone line of defense – hardware level security should become a given. That will need a lot of standardization, which is not a term our industry particularly likes.
  3. Ethics and law needs to be taught to all AI practitioners, and need to become part of the curriculum in early education. Awareness of the distinction between good and bad usage of AI need to become a minimum requirement.

AI Project team structures will change


Math and coding skills are not enough to do AI projects well. This is not new – we have already known this for a while. I think we will start seeing teams organized in four overlapping specialized groups going forward.

Most AI roughly follow the same cyclical sequence .

  1. Understand ( language, sound, vision, smell, touch etc) and Organize information from the environment
  2. Reason using math and logic , and make trade-offs and come to decisions
  3. Interact with humans and/or machines to convey decisions (UI, psychology, visualization etc) and collect feedback
  4. Learn from results on how the decisions worked and tweak how the problem will be solved from now on

Today, we try to do all of this with very little specialization – except perhaps in the math/logic side, and industry domain knowledge. But that won’t sustain going forward to cope with the scale – each area will need specialization and a lot of collaboration with each other.

Academia and Industry will become indistinguishable

There are two things an AI team needs to stay cutting edge – quality of AI talent , and quality/quantity of data available to make the solutions smarter.  No surprise then that most of my time gets spent finding and retaining such talent. This is true for all my peers across the industry too . If there is one set of people who are under even more stress than us in the industry – that would be the leaders of top universities. Industry and Academia has generally had a good working relationship historically , but the war for AI talent has Industry aggressively poaching AI talent. This might be great for the short term – but absolutely horrible for the long term. Who will teach the next generation if industry keeps poaching the best teachers and researchers ?

Academia has started great initiatives to let professors go to industry and come back – but not in a mainstream way as far as I can tell. And industry has not – in a mainstream way – gotten into the habit of thinking of academia beyond special projects and consulting. This is not an AI specific problem – AI will just make it painful enough for both sides to get to a solution quickly. I think what will happen is a de-facto working arrangement where there is little to no difference between academia and industry in the field of AI with experts just wearing different hats as needed.

Happy holidays !