I often get asked to prepare and deliver customer presentations on specific technology and business challenges. Not surprisingly, one of the most common requests these days is on “AI”. In the context of AI, this is more often than not, trying to de-mystify what AI is and what it isn’t amidst a level of exposure and publicity that no other technology shift has ever had placed on it. I lead this discussion with a quote that shows the magnitude of change that many are considering is correct:
“AI is far deeper and more powerful than just another technology. The risk isn’t in overhyping it; it’s rather in missing the magnitude of the coming wave…
…We really are at a turning point in the history of humanity.” Mustafa Suleyman, Co-founder Deepmind.
Whether Mustafa’s assertion is correct or not, unfortunately many people and organizations have simply forgotten some of our basic rules and principles of IT productivity and efficiency – deploying technology without the right and appropriate level of business change will not deliver the outcomes expected. It would seem if I read what I am given, that by implementing a Generative AI strategy, nothing else is required to enable success. This is clearly not true.
The predominant factor, it is suggested, for an organization to be successful is agility. In turn, the only way to be agile is to combine technology with people/business change. Decoupling either technology or people/change will deliver only sub-standard results.
Two specific quotes that back up the need for agility:
“Agility is created by people. People that are going to go after those conventions and try to tear them down, but are mission focused, that get the job done no matter what it takes. And it’s the culture that those people create that ultimately get the job done. So, we can’t make an org chart or process for agility.” Will Roper, USAF.
“In today’s era of volatility, there is no other way but to re-invent. The only sustainable advantage you can have over others is agility, that’s it. Because nothing else is sustainable, everything else you create somebody else will replicate.” Jeff Bezos.
To summarise the challenge – will the trending AI solutions be able to replace some or even all of the required human interactions and therefore make that organisation more successful without the necessary increase in organizational agility?
The AI team would probably say “well, yes of course, the use of AI and its generative capabilities will mean that an organisation can not only make decisions quicker, but it can also see challenges quicker than anyone else and propose strategies to combat them”. This sounds like utopia – I simply switch on my AI-bot, let it go to work, and I can sit at home whilst it makes all the decisions for me.
However, the assertion that AI is the game changer in an organisations level of success can be challenged as follows:
– The only way an organisation is going to be successful is to be agile. In this context, agility has a very simple meaning – i.e. an organization can change and adapt based on the triggers that are being observed. Conversely an organisation that is not agile will remain less and less aligned to those triggers that will make it succeed. There is a direct correlation between an organisation being successful and it being agile.
– Technology doesn’t create an agile organisation, people do. The assertion is very simple; technology is an enabler not the outcome. Generative AI will assert it creates the outcome, however the requirement is for an outcome to make an organisation more agile and that is a combination of technology that can be more agile so that “people” can use those enablers to change the organisation.
– The term “people” includes resourcing, skills, culture, and right sizing at a minimum. Skilling up a workforce with the backdrop of AI can be seen as very challenging – how far would an organisation want to “outsource” the intelligence to a piece of Machine Learning code rather than be an intrinsic piece of knowledge held by the staff. It could be very tempting by a CEO to de-skill and reduce a work force considerably in the areas that will be gaining the benefits of the new technology.
– Which is going to be more successful:
1. Organisation A – has invested and deployed a significant amount of AI but without any business context or ability for the people to exploit it.
2. Organisation B – has invested in people, culture and change but is lagging on deploying technology.
– There is no doubt that working for Organisation A will be exceedingly more interesting that Organisation B and there will always be a hope that Organisation A will start investing in the right people. Working in organisation B will be very frustrating. Employees in organisation B (and recruitment could be very challenging as well) will take a view that despite the investment in themselves will feel the company isn’t investing correctly and won’t succeed. Attrition will be high as well.
– With these two extremes it will be Organisation B which will be more successful.
– Logically a successful organisation will have the right balance between technology (AI) and agility.
Cisco recently published a major double blinded survey on the “readiness of AI”. See https://www.cisco.com/c/m/en_us/solutions/ai/readiness-index.htmlfor more details.
The summary which may not be a complete surprise is that despite an overwhelming proportion (97%) of surveyed organisations having an “urgency” to deploy AI, a very low 14% are ready integrate AI into their business.
One major warning trigger is the relentless focus of deploying technology (AI) without the organisation understanding it and, in that context, there will be a significant amount of wasted and frustrated investment. Therefore, in advance of any technology deployment, there must be a realistic skills assessment performed so that the solutions that are deployed can be used to their maximum capability. An interesting anti-pattern can occur here. Without the right foresight, it could be assumed that by enabling more automation, more complex prediction management and even self healing solutions, the workforce could be de-skilled. However, there is a realisation that rather than de-skilling, there is an up-skilling requirement in order to ensure these solutions are deployed to their maximum benefit.
In conclusion, for AI and its associated components to be successful within an organisation, there needs to be focus on both the technology strategy coupled with the assurance that the people (with the correctly placed skills) and cultural ecosystem are positioned to use it to its greatest potential.
Neil's thoughts 