RPA Is Just One Piece of the Automation Puzzle

With any technology experiencing massive adoption, there is no shortage of unwarranted hype. RPA is no exception as it has been the fastest-growing enterprise software category for the last three years. But, beyond the hype, RPA does deliver significant value and can radically transform how your enterprise works. You just need to realize what to expect of RPA before it’s unleashed.

Hype Leads to RPA’s Perceived Failure

The biggest fallacy fueling RPA’s hype machine is the term itself. It is not robotic process automation. More accurately, it is robotic task automation. The misnomer is responsible for some of the challenges the technology has faced in terms of scaling across the enterprise. The vast majority of companies that have deployed RPA still can’t get more than 10 bots into production.

Another major misperception for RPA is that automation will reduce operating costs by eliminating headcount. There is no doubt RPA does enable a team to do more with less, but promises of fewer resource requirements too often fail to materialize. Companies need to think more about the impact on employee experience and the value those employees deliver. RPA does a great job of automating low-value work so employees can focus on high-value activities. 

Finally, despite its reputation as a panacea for many enterprise ills, RPA often adds to an organization’s technical debt, which will eventually be a problem someone has to correct. There is no doubt RPA is fast, efficient, and less expensive than other methods. But, it’s more of a band-aid than a cure. 

For example, with analytics workloads, in particular, data is often generated in legacy mainframes and RPA is used in place of costly API integrations and other fixes. It provides a temporary fix to get a few more years out of a legacy system. Yes, it avoids a costly, time-consuming, and error-prone system upgrade. But it ignores the less obvious costs and inefficiencies associated with maintaining the legacy application, like performance, compliance, and security. These issues would typically be addressed by an upgrade but are too often pushed off by deploying RPA as an interim solution. 

Focus on Automation’s Value

The grand promise of RPA so frequently falls short due to over planning, the inability to identify key automation opportunities, and a disproportionate focus on short-term objectives to show wins even if they’re not aligned with corporate objectives. This is why many organizations spend 12-18 months before getting a single bot into production. 

Today, automation is the new transformation. After a decade or more of mediocre success rates and an overemphasis on customer experience initiatives, automation provided needed relief to address the transformation fatigue that many companies faced. Fortunately, RPA is not the only automation technology available to drive business value. 

Automation technologies are quite flexible and are being implemented across a wide variety of settings, from structured transactional activities to end-to-end processes. Use cases across the enterprise can be addressed using a variety of technologies. In addition to general user interface (UI) layer tools like RPA, there are domain-specific tools available to support various functions, like marketing automation. Other tools focus on data extraction to capture unstructured data and make it more usable. Technologists also have digital process automation platforms available to address deeper and wider workflows, and more traditional APIs can be used to integrate enterprise systems.

4 Automation Prerequisites

Regardless of the automation technology deployed, there are four vital actions to take before your company or department invests time, energy, and budget into a project. 

  1. Assess the overall process complexity. Insights on the applications involved and the amount of human expertise required will help guide technology selection and determine the feasibility of success. 
  2. Decide if the process is mission-critical or if you are automating just for the sake of automating. 
  3. Identify key metrics that will define a winning result. Whether it is speed or scale or accuracy or efficiency, you want to establish the goal in advance so you know when you can celebrate. 
  4. Proceed only with fully detailed process documentation. To improve tomorrow, you need to understand where you are today. It’s common sense. No one says they are going to lose 20 pounds but do not know how much they currently weigh. Unfortunately, too many organizations try — and fail — to automate a process that they do not fully understand how they complete today.

It all makes sense. Before you begin, you need to know where you’re starting from, where you’re going, and how you’re going to get there. Automation is no different. And, if you truly want to succeed in transforming how your business operates, you must realize RPA is just one piece of the automation puzzle.

The Low-Code Movement Will Spur Process Intelligence

Interest in low-code development is skyrocketing. Annual market growth is predicted to exceed 25%, growing from $13B in 2020 to $65B in 2027, according to research from Brandessence Market Research. For organizations looking to win in the digital-first agile world, low-code is quickly becoming a critical component of a modern enterprise technology stack. If you’ve been around technology, you have probably heard the phrase, “Faster, better, cheaper — pick two.” But low-code gives you all three and adds “flexible” to the mix.

With their roots in the Rapid Application Development (RAD) tools of the 1990s, low-code platforms are an application development environment that use graphical user interfaces and configuration instead of traditional hand-coded computer programming. Formal software engineering skills are not required to create applications since a visual user interface in combination with model-driven logic is used. This opens the door to a wider range of people who can build apps for the business. With a little training, employees can rapidly create and deploy secure scalable software. One note to remember – low-code is not interchangeable with no-code which is a subset of technologies aimed at business users primarily working on enhancing their individual productivity.

A New Player in the Enterprise Technology Stack 

It’s impossible to argue against the need and demand for low-code in the enterprise. According to Gartner, more than 65% of application development in 2024 will be performed by low code platforms. That’s a remarkable shift for a software category that did not exist a decade ago. The number of digital applications and services being built is exploding as well. Between 2018 and 2023, more than 500 million apps will be created according to IDC. To put that massive number into perspective, that’s more than the previous 40 years combined. With low-code, companies can rapidly produce applications within a shorter time span and at a fraction of the cost. Schneider Electric launched 60 apps in 20 months, delivering most in just 10 weeks, and Ricoh replaced critical legacy systems 3X faster with a positive ROI in 7 months using Outsystems. Some skeptics may point out the lack of available IT resources, but business users can learn low-code development methodologies quickly, typically in less than one month. Clearly the old way of building apps cannot keep pace with today’s digital marketplace. 

Process Intelligence Jump Starts Low-Code Journey 

To help accelerate utilization of low-code and scale it across the enterprise, process intelligence is a key enabler. You cannot improve how you operate tomorrow if you don’t fully understand how you work today. And most companies truly don’t understand how they operate on a daily basis, especially at a granular user activity level required to automate a process or streamline a workflow. They have limited process understanding. They don’t know how their applications and data interact, and they don’t really understand what their customers expect.

The impact of this gap in process data is well documented. The 70% failure rate of transformation programs is widely reported. McKinsey pegs the cost at nearly $1 trillion annually and noted on 14% of companies have seen a sustained and material improvement in their business. Another study from Gartner noted only 1% of companies have sufficient understanding of their processes to take full advantage of the technology solutions. 

Before embarking on a major initiative, a company must map its processes, its systems and its experiences. Today, that necessary level of operational intelligence just does not generally exist in most companies and on top of that it is very difficult to obtain without process intelligence.

Low-Code and Process Intelligence – Better Together Than RPA

Process intelligence was a similar catalyst for Robotic Process Automation (RPA), but the opportunity with Low-Code is even greater. RPA programs enjoyed massive early uptake, but the challenge was how to scale the initiatives. Companies still struggle getting more than 50 bots deployed. Once any obvious low-hanging fruit is automated, it becomes difficult to identify what to tackle next and how to tackle it. Process intelligence answers those questions to help scale RPA. 

With Low-Code, Process Intelligence accomplishes that and more. The combination will overtake RPA as the gateway for AI and automation. Low-Code is more efficient and scalable than traditional RPA development because it does not operate at the user interface (UI) layer, making the applications more resilient. Additionally, where RPA is traditionally limited to task activities, Low-Code is much more capable of handling sub-process and process level activities making it much more valuable to the enterprise. Coupling Process Intelligence with Low-Code helps steer an enterprise toward a next-generation operation model that is faster, cheaper, better and flexible. It may also fully realize the promise of Citizen Developers that RPA struggles to achieve.

Life Sciences Accounting & Reporting – Mind the Process Data Gap to Win in 2021 and Beyond

The 17th annual Life Sciences Accounting & Reporting Congress brought together the who’s who of industry leaders to share insights and help navigate the year ahead. From addressing top-line regulatory actions to discovering solutions for industry-wide challenges, the can’t miss event offered technical education coupled with organizational growth strategies. Hopefully the top-notch faculty and industry experts will be back in-person in Philadelphia for next year’s event.

I participated in an “Ask the Expert” panel with PwC’s Michelle Lee, Deloitte’s Temano Shurland and SAP’s Robert Jenkins to discuss practical applications of today’s technologies to finance and accounting, as well as insights on scalability towards tomorrow’s digital breakthroughs to transform accounting and financial reporting.

Two items from the news caught my eye as I was preparing for the session. First, you had Microsoft announce they will be giving away their low-code Power Automate application free with Windows 10 — which has one billion monthly active users according to some estimates. And second, The New York Times did a major story on Robotic Process Automation (RPA) technology which signaled to me the tech is truly mainstream now. Given the audience (and I could not make this up if I tried), the article was titled, “The Robots Are Coming… for Phil in Accounting.”

Looking at the modern finance agenda, it is safe to move beyond the automation talk track of the past few years and explore what’s next and how to get there. Transformation is still top of mind. Everyone is trying to do more with less, leverage new technologies, enhance compliance, improve experience, be more data driven and any of the other targeted outcomes.

What is worth considering is the miserable success rates of major change programs. 70% of digital transformation projects fail, wasting $900B annually. Just 14% of companies have seen sustained and material performance improvements from their transformation programs. And finally, one more statistic, only 1% of organizations have their processes sufficiently under control to realize the full potential of digital solutions.

It really makes you wonder why programs can still get funded at all. I can only think that the potential risk of doing nothing is even greater, and it is seen as a long-term threat to the viability of the organization.

 So what can be done to get better faster?

We’ve been taught over the years that project success relies on people, process and technology. But the shift to a more digital-first approach over the past decade has broken the golden triangle of people, process and technology.

There has been way too much emphasis on technology as the answer to our company’s problems. And that has been at the expense of the people and process dimensions. Technology was seen as the easy button. Go buy a new platform and everything will be better.

I used to regularly conduct technology assessments. In at least 8 out of 10 assessments, where I was brought to explore what was seen as a technology problem. The companies had acquired the right software for their business. The root cause of the problem was actually a process issue or training/people issue that was not addressed properly. But the team was always convinced there was a technology problem.

But it is more than just too much focus on technology. And this is my final point. The biggest obstacle to complex, large-scale change is the lack of detailed knowledge on current state operations.

Companies need to evolve to win the market – and that’s probably more true today than ever before in the current environment. But they truly don’t understand how they operate on a daily basis. They have limited process understanding; they don’t know how their applications and data interact, and they don’t really understand what their customers expect.

And if you step back and think logically, it’s pretty obvious. It’s really hard to go from Point A to Point B if you don’t know where you are actually starting from. Everyone wants to get to that magical future state, but you need to understand current state first.

Before embarking on a major initiative, for it to be successful, a company must map its processes, its systems and its experiences. Today, that necessary level of operational intelligence just does not generally exist in most companies and on top of that it has been traditionally very difficult to obtain, but that is starting to change with emerging technologies which I’ll get into deeper in the break out session.

Most people are probably familiar with manual process mapping and conducting time-motion studies with consultants or business analysts. There are technology alternatives to make this process cheaper, faster and better.

Elevate Human Potential With Innovative Automation on the hello, Human Podcast

Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we investigate how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We strive to make each episode intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.

FortressIQ | Intelligent Insights for the Modern Enterprise
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How Humalogy Measures the Human/Technology Balance on the hello, Human Podcast

Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we investigate how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We strive to make each episode intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world. 

Episode 6 – Humalogy and The Future of Work

FortressIQ | Intelligent Insights for the Modern Enterprise
Episode 6 - Humalogy and The Future of Work
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We’re Bringing FortressIQ to Japan with Hitachi Solutions, Ltd.

We’re very excited to announce a new relationship with Hitachi Solutions, Ltd., a Tokyo-based provider of digital transformation solutions and services. Hitachi Solutions, Ltd. is now using FortressIQ Process Intelligence as a customer, and will also offer the FortressIQ platform to their own customers to visualize and modernize complex business processes. This relationship marks our entry into Japan’s market at a time when regional demand for migrating work to the cloud is accelerating.

Our partnership with Hitachi Solutions, Ltd., enlists the company as a reseller of FortressIQ Process Intelligence in Japan. The platform will help our joint customers decode work and make data-driven decisions to improve competitiveness well into the future. Internally, Hitachi Solutions, Ltd., is already using FortressIQ to identify, analyze, and visualize business processes as they work to eliminate bottlenecks and gain efficiencies. 

Transformational Growth for Process Intelligence

Hitachi Solutions, Ltd., has long been a conduit for quickly moving enterprises along their digital transformation journey. The company’s use of cutting-edge digital technologies, such as artificial intelligence (AI) and Internet of things (IoT), successfully guides customers as they renew and modernize business processes and speed their move to the cloud. 

Modernizing work and shifting more effort to the cloud is particularly important in Japan. The country’s aging workforce is forcing companies to seek out dramatic increases in efficiency and productivity to sustain market growth. But, companies must first understand how their business operates today. That’s driving huge demand for process intelligence across Japan. ITR, a Tokyo-based market research and consulting firm, projects this industry to grow from ¥400 million ($3.8 million) in 2019 to more than ¥7.5 billion ($71 million) by 2024. That’s an increase of 1,775% in just 5 years. 

Japan’s market offers a greenfield opportunity for process intelligence, and this new partnership will position us to take a commanding lead with a strong, first-mover advantage.

Adding Microsoft Power Platform

Hitachi Solutions, Ltd., is using the insights gained with FortressIQ to help customers migrate business applications from on-premise to the cloud, which is further accelerated by their partnership with Microsoft and their use of the Microsoft Power Platform. Power Platform brings together Microsoft solutions, from Office 365 and Dynamics 365 to Azure and hundreds of other apps, to enable the creation of end-to-end business solutions. Component tools, such as Power BI, Power Apps, Power Automate, and Power Virtual Agents, empower companies to build custom apps without coding and automate processes to streamline how their business operates. 

We’ve been working with Microsoft Power Platform for quite a while as our integrated solution helps organizations increase productivity by automating repetitive, time-consuming tasks. Our end-to-end solution for intelligent automation provides cognitive process intelligence, AI-enabled workflows, and deep business insights, and does it all faster than the traditional alternatives.

Leveraging the Speed of Process Intelligence

The AI power behind FortressIQ provides unmatched speed and accuracy over the typical process discovery and mining methods. This gives Hitachi Solutions, Ltd., and their customers a faster path to realizing the benefits of process modernization. According to Hitachi Solutions, Ltd., using FortressIQ has made it possible to automatically analyze end-to-end enterprise business processes and visualize real results in as little as 2 weeks. And, that’s without disrupting workers or conducting tedious analysis of application logs.

You, too, can have that speed, whether you’re based in Japan or anywhere else in the world. To learn more about our new partnership with Hitachi Solutions, Ltd., and how the company is using FortressIQ and Microsoft Power Platform with customers across Japan, visit hitachi-solutions.co.jp/wsi/sp/.

Forrester, Microsoft, and the Future of Automation on the hello, Human Podcast

Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we investigate how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We strive to make each episode intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.

Episode 5 – Understand Today, Automate for Tomorrow

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Data, Context, and Domino’s (pizza) on the hello, Human Podcast

Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we investigate how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We strive to make each episode intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.

Episode 3 – Rebooting Data – to – Decisions Initiatives

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In episode #3, my guest was Doug Henschen, Vice President and Principal Analyst at Constellation Research. Doug has a unique view of the business world, since his firm is focused on helping early adopters leverage disruptive technology. The top 5%, as he puts it. In our conversation, he shared what those pioneers are doing in process orchestration, how it helps companies manage new information, and how AI can elevate the customer experience. And, believe it or not, we talked about Domino’s Pizza. But we started with a look at the digital transformation acceleration that’s happened across 2020.

“We often hear that in the last six months, companies have done more digital transformation than they did in the past six years,” said Doug. “It’s all about getting more agile, getting more data-driven. It’s put the move into the cloud on steroids. The companies that are ahead of the curve are in a good position.”

But being ahead of the curve takes more than just moving to the cloud, according to Doug. Every company is swimming in data these days. So there’s a dire need to manage that data, understand it, and put it to use in valuable, impactful ways. But it’s going to take a mix of technologies and humans to do it well, and the approach has to be unique to each enterprise. 

“I think we’re going to see platforms on which people will start to build very custom applications,” Doug explained. “Instead of these standardized enterprise applications, they’re going to build more and more. (Their needs are) just too unique to the organization to have a commercial software vendor provide that application. Companies are going to be using this mix of technologies to build their own applications and experiences on top of what I’d call intelligent orchestration platforms.”

Of course, humans will lead the orchestration, but it’s becoming more and more clear that machines will be part of the decision-making process. Doug noted that it’s been almost a decade since IBM’s Watson won on Jeopardy. But the promise back then of artificial intelligence (AI) leading us to huge advancements has yet to materialize. Instead, much of the context behind the data or alongside the decision remains understandable only to humans. So AI might make a recommendation that humans then use to make a better decision. But that then invites human bias, errors, and inconsistencies.

“It’s not just about the data; you really have to know something about it,” added Doug. “It’s the metadata around that data. Who is this customer? What is their history? What is the stage of the process they’re in? When did we talk to them last? Do they have a service issue that’s unresolved? Are they near the end of their contract? It’s not just data, it’s the context around the data.”

“That’s one reason I’ve been doing a lot of research and been advocating embedded approaches of next-generation applications that bring the data and the context right into the context of the application. You have both a human understanding and machine understanding, and you can drive better actions, whether those actions are carried out and executed by a machine or by a human.”

Doug gave a great example of this type of contextual understanding using Domino’s Pizza. They’re taking an innovative, data-driven approach to not just back-end ordering, inventory, and operations, but also using those same insights to elevate the customer experience with increased visibility and interactivity. Progressive financial services institutions, such as Capital One and Rocket Mortgage, are doing the same, and crushing the competition with a stellar customer experience based on data and context. 

Again and again, we’re seeing that AI is at its best when used to augment human abilities, especially in human-to-human interactions like customer service. Technology is a huge help, and it takes much of the burden off of workers, making them more efficient and productive. But, in the right context, there’s not yet a match for putting a real human on the line with a customer in need. 

“Sometimes you might have to take the (digital) agent offline and switch in the human because something is happening dynamically in the business environment,” said Doug. “That’s what we see ahead. The progress is now happening, where it’s overall monitoring of the process, not just adding more and more bots to have silos of automation.”

There’s much more to my conversation with Doug on the hello, Human podcast. You’ll also hear his favorite resources for staying current on the latest technologies. Or, you can read the full podcast transcript here.

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Using AI to Turn Talent into Competitive Advantage on the hello, Human Podcast

Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we explore how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We want each episode to be intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.

Episode 2 – Turning Talent into Competitive Advantage

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In this episode, I welcomed Kamal Ahluwalia, President of Eightfold AI. The company’s Talent Intelligence Platform helps organizations retain top performers, upskill and reskill their workforce, recruit top talent, and reach diversity goals. But what makes their solution different is the use of deep learning artificial intelligence. The company’s technology scours publicly available information from around the globe to understand what people are truly capable of doing, which enables companies to then hire, promote, or reassign based on potential.

“Resumes are all backward-looking,” said Kamal. “What people are looking to do, and how we want to use our AI expertise, is to allow the hiring companies to hire for potential. What we have done with our data-driven platform is that we should be learning from all the skills and capabilities that are out there.”

As Kamal explained, the past work of any individual needs context, but also doesn’t necessarily dictate what you can or can’t do in the future. Determining that context is important, but first they need to understand what defines the context. And, even in that same context, different people have different career goals and aspirations. Eightfold’s technology works to understand all of these combinations, and adds intelligence to help reach diversity and inclusion goals, too. 

“If we keep looking for people who have already done it before, clearly, we haven’t given enough opportunities to people of diverse backgrounds and people who don’t have the same privileges we have had,” said Kamal. “This applies to pretty much every segment. The way to get out of that is to look at the whole thing holistically. Our algorithms don’t take anything into account, whether it’s sex, background, ethnicity, pedigree, any of those things when an individual is being compared to a particular job. So when we are presenting these few people who are a great fit for a role, it is only based on what they’re capable of doing.”

Eightfold’s technology further helps companies create job descriptions that eliminate bias and focus on getting the right person in the right role. But it also helps identify current employees who would fit that profile, are likely to want to make a move, are in diversity segments, and more. It all helps companies course correct as they fill open roles. 

“Our customers have improved the diversity from 18% to 33% for women,” added Kamal. “Other customers have seen a 90% reduction in time to discover and engage with underrepresented candidates. In all aspects, the number one excuse that is often used is, ‘We looked, but we couldn’t find enough capable people of diverse backgrounds’. We want to use our AI to show that no, you didn’t know how to detect the potential, and we are here to help you.”

The technology created by Eightfold works for job seekers just as well. Applicants can be shown open roles for which they’d be a great fit, whether they’ve considered them or not. And that helps them apply with confidence while increasing diversity applications. 

Kamal and I also discussed the impact of remote work on future recruiting trends. Now that companies are going to be more open to hiring remote workers, it’s going to allow them to increase the size of their talent pool. Naturally, that also increases the number of potential candidates with diverse backgrounds. 

Using AI to help improve how HR works is another area where Eightfold adds value. And a large part of HR’s job is to focus on culture, employee satisfaction and wellbeing, and more. It also helps identify a company’s internal influencers.

“More and more people are being forced to rethink their business, and there is more need for digital sales, data scientists,” Kamal explained. “People are realizing that it’s not like all these markets are littered with that talent, so let’s focus more on the employees. What we are doing with our AI platform is we provide a talent marketplace or a project marketplace where the company can post projects. The important part is how do we get some of the rockstars to participate, and how do we find the experts so that we start building this self-service environment where people want to be appreciated, they want to learn more, or they want to learn from others who are recognized in the companies as being experts?”

The need for specialized talent continues to grow, but the pace of change in the workplace and in technology seems to be in constant acceleration. The situation becomes even more complicated when you factor in the shift to more remote work. Eightfold is taking a unique approach to helping companies fill roles faster with the most qualified candidates. That’s good for everyone, and we’re excited to see how their AI will continue transforming the ways companies attract and manage talent as a competitive differentiator. 

Hear the entire conversation with Kamal on the hello, Human podcast, and learn his favorite resources for staying current on the latest technologies. Or, you can read the full podcast transcript here.

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Pankaj Chowdhry and the Four Realities of Transformation on the hello, Human Podcast

Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we dig into how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We aim to make each episode intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.

Episode 1 – The Four Realities of Transformation

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In our very first episode of hello, Human, we welcomed our very own Pankaj Chowdhry, the founder and CEO of Fortress IQ. Pankaj and I discussed how humans and AI can interact to add more value to business processes, and then explored the four realities of transformation. But, we began where every AI conversation seems to begin: how robots are going to take over and destroy humanity. 

“I think the thing to do is to step back and say, what would make AI different from anything else?,” asked Pankaj. “Any technology that we as a human civilization or a more technology-advanced society, has always had positive and negative to it.”

As Pankaj quickly explained, however, the pace at which AI is advancing is unprecedented. That’s fueling the fears and forcing us to change the conversation by pointing to areas where AI can improve our lives. But, we also need to address the fears which arise as AI changes how we work. The solution, says Pankaj, is in using AI to help workers be more accurate, efficient, and productive in their existing roles. 

“I think a joint solution is always going to be better,” said Pankaj. “When we’re looking at transformation and the reimagining of these job roles, you wouldn’t expect someone to do a job without a laptop. AI is kind of that same level. There is going to be a certain level of interaction with artificial intelligence that every job role is going to have. The key is just to figure out how much of it works and if it actually adds value.”

This joint human-AI solution is where AI is adding real value to enterprises today. AI helps as an assistant, a second set of eyes, or the doer of mundane or repeatable tasks. Humans then have more time or information to perform higher-level tasks and make important decisions. This is where the four realities of transformation come in. As a quick recap, these four points state that your processes, systems, people, and structure might change (for the better!) with AI, but they aren’t going away. 

“When I say your processes aren’t going away, what I’m trying to make sure people understand is that the process is going to exist,” Pankaj explained. “You have to deal with the realities of what your IT landscape is. Any transformation strategy has to embrace the people that are going to be impacted by it because these people are oftentimes the core of what’s going on in the process.”

That’s the classic golden triangle of people, process, and technology. But the fourth one, organizational structure, is where the real challenges to transformation come into play. I’ve read that as many as 86% of transformation projects fail to live up to their performance improvement goals, and just a tiny fraction, a mere 3%, achieve sustainable change. Pankaj points to this fourth reality of transformation as the often-overlooked key to project success: everyone and every team affected by the transformation has to be on board. 

“Any transformation strategy that requires a wholesale change of the org chart on day one is going to be most likely a non-starter,” said Pankaj. “You’re going to have compliance, security, training, HR. All these things need to be taken in so you can make sure the organization you’re building has a very, very clear path of how the existing organization is going to arrive there.”

It may seem counterintuitive that a successful transformation is only possible when embracing both change and the status quo, but that’s why so many transformations fail. Success lies in figuring out how to leverage the existing people, processes, and technology while delivering the desired organizational change. Listen and subscribe to hello, Human to hear my full conversation with Pankaj, as well as his favorite resource for staying current on the latest technologies. Or, you can read the full podcast transcript here.

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