Originally published on the Delta Knowledge blog.
With AI now able to make decisions for us, we don’t need knowledge any more, right? Or people for that matter, right? Right?
- AI is suddenly able to master many of your business processes.
- How well your company manage your staff’s strategic and problem solving capabilities is becoming critical.
- Knowledge, not information, is fast becoming your most valuable asset as human staff focus on solution design and exception management.
- Managing that knowledge will fast become a major focus of boards and executive teams as they avoid the rigidity of legacy business management solutions.
Business scholars and consultants have been encouraging organisations to better deal with change and volatility for decades now. Hauschild, Licht, and Stein captured this well2, “In today’s changing economy, the key to faster, cheaper, and better is to bring the full force of a company’s knowledge to bear on the effort. Knowledge, not land, labor, and capital, is now the lifeblood of a corporation.”
Attempts to move away from scientific management and more toward Peter Drucker’s knowledge economy3 have been undermined by many leaders clutching to traditional linear forms of control such as five-year strategic plans and simple, quantitative metrics and KPIs. Drucker knew this and spoke often about the self protecting nature of power structures. Some companies have gone out of business as a result; either slowly over decades like Kodak or suddenly during the recent pandemic. However, many persist, including in the government arena where competition and profitability pressures don’t have the same import.
Suddenly, a potentially larger fluctuation is on our doorstep, and it’s set to impact every sector, both private and public. The snowball of Artificial Intelligence. I say suddenly, but of course this has been coming in for decades now. However a few things have changed recently as outlined by Bruce Boyes in his recent RealKM article and the uptake of these new tools has been explosive despite various warnings and examples of cyber-security failures4.
Focusing on the future of management
I am interested, not so much in the details and possibilities of tools like chatGPT as I am in how the nature of our management structures will change as trust increases in these AI bots, and automation, design, authoring and analysis get handed over.
For years, companies have rolled out ERPs, CRMs, Workflow and Risk Management tools in order to build and reinforce the organisations ability to deliver the HOW of their business and secure their key value propositions. But until now, much of that focus has been on the manufacturing and service delivery capability. That is where these tools are aimed. As Davenport et al. puts it, “The technologies enabling reengineering in the 90s were primarily transactional and communications-based. They enabled efficient data capture and transfer within and across organizations. AI, on the other hand, enables better, faster, and more automated decisions.”
So now AI-based automation will transform these primarily human “HOW” tasks:
- Software will literally write itself, but who carefully defines the problem it needs to solve?
- Reports will appear at a command, but what exactly are we trying to analyse and understand?
- News articles will be magically written seconds after an event has occurred, but what are the larger strategic implications of publishing that information and if it gets it wrong then will you suffer the same fate as the Silicon Valley Bank5 just did?
Davenport et al. go on to talk about the use of AI at Shell for plant monitoring. This is where it gets interesting: “As a result of these changes, inspectors and maintenance technicians can now rethink their day-to-day work. They can focus on higher-value activities such as prioritizing projects or, if they’re on site, performing more advanced verification.”
Notice here the way the nature of work has changed. It has gone from process work to knowledge work. But here is the thing:
- With process work the nexus of control is on monitoring and compliance – you know people are doing a good job because the process is good and you know it is being followed. Think procurement, risk audits, health and safety, etc.
- But with knowledge work, the capability is based on critical thinking, creativity, advanced problem solving, and many, if not most of these are not repetitive, not measurable against a simple benchmark. So how then do you manage the corporate capability for this?
- Finally, with knowledge work, the focus moves from outputs to outcomes. Something a little harder to both define and measure with numbers on a dashboard.
FYI, Sean Mallon covers these areas in more depth here6. Becoming acquainted with them will help you lead change carefully as good AI opportunities and snake-oil salespeople both come knocking on your door.
So how does knowledge management help?
The discipline of knowledge management has been working for over three decades to try and bring the same improvements we saw in the industrial age to this sphere of knowledge work. Drucker himself foresaw all of this when he said7:
“The most important, and indeed the truly unique, contribution of management in the 20th century was the fifty-fold increase in the productivity of the manual worker in manufacturing.
The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and knowledge workers.”
Unfortunately (with the exception of many startups), as mentioned above, the bulk of the last two decade’s CEOs and leaders have failed to do this. By classifying and measuring managers, engineers and designers as glorified factory workers, they have eked out a few extra years profit for their companies, but often at the cost of adaptability, innovation and employee satisfaction. Michael Simmons wrote an excellent little article8 about the need to solve this if you want to dive deeper, but the problem is even worse because most MBA programs are still churning out graduates of this old style of command and control combined with legislated finance tools like activity based accounting that restrict what needs to be reported to the government.
With the introduction of mainstream AI tools, suddenly the pressure is on. We are going to see more and more roles focusing on these creative, knowledge tasks and competencies mentioned by Sam above. My question is simple:
“Is your company as competent at managing your knowledge and intelligence capability as it is managing your current tangible assets and processes?”
If not? You might have some thinking to do before this giant snowball picks you up and rolls you to the bottom of the hill.
So, far from replacing KM, I predict the uptake of artificial intelligence will mean that managing the tacit knowledge, soft skills and local specialisations of their workforce will become one of the most important tasks of every board and C-Suite on the planet. Well, at least the ones that want to stay competitive.
Article source: Will A.I. make managing knowledge more or less important?
- Davenport, T. H., Holweg, M., & Jeavons, D. (2023). How AI Is Helping Companies Redesign Processes. Harvard Business Review. ↩
- Hauschild, S., Licht, T. & Stein, W. (2001). Creating a knowledge culture. The McKinsey Quarterly, 1, 74-81. ↩
- Hayes, A. (2021, January 22). What Is the Knowledge Economy? Definition, Criteria, and Example. Investopedia. ↩
- Maddison, L. (2023, April 4). Samsung workers made a major error by using ChatGPT. TechRadar. ↩
- Snow, R. (2023, April 14). What Caused the Silicon Valley Bank Collapse? DailyFX. ↩
- Mallon, S. (2022, November 28). 7 Jobs Humans Can Do Better Than Robots And AI. SmartData Collective. ↩
- Drucker, P. F. (1999). Knowledge-worker productivity: The biggest challenge. California management review, 41(2), 79-94. ↩
- Simmons, M. (2022, March 14). In 1911, a genius revealed a forgotten science of how to be 50x more productive without working more hours. Medium. ↩