Workato — Connect your apps. Automate your work. | Workato

Summary

2023’s mix of economic headwinds and AI momentum set the stage for another year of change. Companies are rapidly adopting AI, and their investments are paying off. Automated processes with generative AI have exploded by 500% in the last year alone.

The outcomes have been staggering. Companies report exponential outcomes across team productivity, demand generation, security, customer experience, and more.

The data shows companies are drawing on a mix of new technologies and a new mindset:

AI and low-code automation are emerging natural partners in businesses. Their combined forces in businesses are interweaving digital brains (LLMs) throughout business processes.
A new automation mindset that embraces agility, systems thinking, and inclusiveness is on the rise.

In this report, we share real data on how organizations are revolutionizing the way they work with AI, automation, and integration, and what that means for their work in 2024.

This data is based on real, anonymized automated process data collected in 2023. For more detail on the methodology behind this research, see Appendix 3.

Top 8 Takeaways

The most noteworthy insights from this year’s report

Generative AI is skyrocketing by 400% in business processes

Processes with generative AI grew by 400% in 2023, and generative AI endpoints grew by 500%.
Revenue and IT operations lead generative AI adoption

Revenue operations is the top adopter of gen AI with 48% of processes, and IT is in second place with 31% of use cases.
Customer retention is the #1 growing strategic priority for automation

Customer support & operations experienced 226% growth in automated processes in 2023.
Operations roles are automating more processes than any other group

Business operations teams automated 27.7% of all processes in 2023 - more than any other subgroup across IT or business teams.
44% of all automated processes are built outside of IT

Democratization and the citizen development trend continues to show strong stability as more automation work is handled by teams outside of IT.
Automated processes are growing more complex

Over time, we are seeing a consistent trend that processes connect to more apps, involve more steps, and require more sophisticated logic.
Multi-department automation is at an all-time high

Over 50% of companies have automations in 4 or more departments, more than we have ever seen in the history of this report.
11% of automated processes in 2023 include humans "in the loop"

A large percentage of automated processes are designed for human interactions, such as approvals or exception handling.

Chapter 01

The AI Trend: Revenue Operations and IT are Leading the Race to AI Impact

Processes with generative AI grew by 400% in 2023

“With AI, and generative AI especially, the possibilities are tremendous. There is so much opportunity in so many aspects of our enterprises to automate across the board.”

Rama Akkiraju

VP of AI at NVIDIA

IT and revenue operations are the early adopters of generative AI

Use cases in generative AI are heavily concentrated in the front and back office. This is consistent with the macroeconomic trend driving companies towards efficient growth. The use cases are also consistent with gen AI’s strengths at content generation (such as email drafts), or content interpretation (such as conversation intelligence call summaries).

Revenue operations are surging in AI innovation, with 48% of all use cases. To “do more with less,” companies are using AI to drive profitable growth.

31% of all AI use cases are in IT operations. Gen AI’s strengths in understanding and interpretation have wide uses in helpdesk and service ticket functions for line of business IT.

“We have applications of AI and generative AI across our entire business, from our supply chain to customer experience and everything in between. From merchants to the finance team, everyone is experimenting.”

Anshu Bhardwaj

SVP and COO at Walmart

A minority (less than ⅓) of generative AI automations are in technical teams

“This technology is no longer in the hands of a few key gatekeepers. This is business-led technology. We operationalize it to create value and introduce a different level of mindset to our organization.”

Darryl Maraj

CTO at TBC Corporation

Much has been said about the democratization that will be brought on by generative AI. While AI has been around for 30 years in various forms, it has been the domain of data scientists. Now, the creativity of business teams is being unleashed with the recent democratization of AI largely led by OpenAI.

This drastic change we have seen in business will only continue, and will serve to expand the democratization trends we are seeing in the following chapter

Chapter 02

The Citizen Developer Trend: The Role of IT is Changing and Democratization is Growing

Everyone is automating their work, regardless of technical skill

This data is a snapshot of the transition point between the low code/no code movement and the new era of AI - IT maintains a slim majority of all automation, but business teams have taken on an enormous share of the workload that just five years ago would have been unimaginable.

IT is evolving into a player-coach role: 56% of automations are still built by IT personas, but IT is also being tasked with governance and guidance for the 44% handled by business teams.

Business team automation activity is at an all-time high: Business teams are on the verge of a majority, and In 2024, we expect to see the scales tip thanks to generative AI.

“The democratized approach is real. Orgs of any size are leveraging automation in multiple business teams. In mature orgs, the number of non-IT skilled employees automating work is almost on par with IT.”

Massimo Pezzini

Head of Research at Workato

Democratization is unmistakable in every company size. From emerging startups to Fortune 500, the democratization trend holds steady - demonstrating that organizations are recognizing the value of scaling their automation efforts outside of the limited scope of a small group of technical experts.

Big Ops has overtaken the big data trend

The citizen development movement is led by operations teams, or “big ops”.

By a sizable margin, business operations roles are the largest group automating work in 2024

27.7% of business operations and 18.8% of IT operations roles combined make up 46.5% of all automation work. This reinforces Scott Brinker’s theory of the era of “Big Ops” overtaking the previous era of big data. In this case, the big data focus is represented by enterprise, solutions architecture, and business intelligence roles which only include 19.9% of the total.

"While each of these ops specialties is a small revolution within its respective field, the collection of all of them is a much larger seismic shift."

Scott Wrinkler

VP of Platform Ecosystem at HubSpot

Front office teams embrace more citizen development than back office teams

Automation is more democratized in customer-facing (front office) functions like revops or customer support. Revops, in fact, is the first group with a business team majority for automation. It is no surprise that IT or product teams have more technical involvement in their work. HR and finance, on the other hand, are still more likely to lean on IT for help with automation. This is consistent with recent Gartner survey data, which suggests that more HR leaders have shared leadership of their technology with IT than not. This data suggests that in areas of the business where processes are more ever-changing, business teams are more likely to have more involvement in automation than in places where the processes are more stable.

“People are happier with automation, especially if you empower the business. One of the best people on my team was stocking grocery stores a few years ago, now she’s building automations with our VP of sales.”

Carter Busse

CIO at Workato

Business teams are automating more complex processes than ever

As we’ll cover in chapter 3, automated processes are growing more complex. Automations led by business teams are becoming more complex as well. This points to two trends: application stacks continue to expand, adding more steps to end-to-end processes, and business teams are upskilling, becoming more capable of automating more.

Democratization drives scale and impact

There is a direct correlation between the amount of builders (technical or citizen developer) a company empowers, the diversity of personas that are empowered, and the degree of automation in the company. The simple math is that the more people with the power to automate, the more they will execute on their creative ideas.

Adopting low code automation leads to more democratization over time

Democratization does not happen overnight. In the first year with low code automation, the average company still has nearly 69% of their automation handled by IT. By year 3, however, business teams take on nearly 48%. As generative AI gains steam, we can expect this timeframe to shrink; While the learning curve for low code is simpler than code, natural language is even less.

Chapter 03

The Tool Sprawl Trend: Addressing Tech Stack Complexity

Automated processes are more complex, reflecting the modern tech ecosystem. We scored process complexity on a scale of 1-10, with a 1 being a simple point to point app integration, and a 10 being a highly complex process with logic, multiple apps, and dozens of actions. This year, 61% of automated processes are considered complex or highly complex (scoring 5 or higher), vs. only 45% two years ago.

Highly complex automation has nearly doubled. Highly complex processes (Scored at 7 or above) has grown from from 13% to 24% over two years. Companies are contending with tool sprawl, more complex markets, and more nuanced challenges than ever before.

“The app stack in companies is growing fast. The quantity of automation tools is growing too. Each new tool promises to reduce fragmentation, yet rather than breaking down silos, we are creating new ones.”

Vijay Tella, Massimo Pezzini & Scott Brinker

In the New Automation Mindset

More automated processes are in multiple departments

One of the ways companies are tackling complexity is by reducing point-to-point integration. Instead, the data suggests movement towards end-to-end process automation. When we look at the year-over-year data of how many departments are automating business processes, the graph is nearly inverted. One year ago, only 19% of companies had automation in five or more departments. Now, that number has nearly doubled to 37%. Companies with automation in three and four departments have increased, while companies with automation in one and two departments have decreased. Notably, this data also highlights that 74 percent of teams are leveraging enterprise automation in more than one business team, and 52 percent in four business teams or more.

“How do we mature from point-to-point to end-to-end integrations? [That question] gives us an opportunity to look at where we can continue to automate and scale the organization.”

Kim Huffman

CIO at Workiva

Enterprise automation includes multiple approaches

Transformation strategies are now cross-silo

More companies are automating cross-department in year one. For years, the traditional pattern has been to automate a simple point-to-point process, then grow it over time. Now, the paradigm is changing, and more companies are automating multi-department processes from the start.

“Automation works across all areas and all aspects of the business, whether it be back office, or operations, or with the customer. Automation is really a necessity if we want to achieve our strategic goals.”

Gabriel Enright

Integration Architect at Vodafone

Over time, digital transformation programs automate more complex processes

Even though more companies are automating more complex processes sooner, automations continue to follow the trend that they become more complex, and companies will tackle more complex automations over time.

To deal with tech sprawl, companies are calling on both business and IT teams

The sheer volume of work and connections that need to be formed across the company are a key driver for the democratization that we discussed in chapter 2. This is evident when we look at the process complexity curves that describe business and IT teams. Business teams are automating slightly less complex processes, and the most complex ones (scoring 8 and 9) are nearly exclusively owned by technical teams. However, the load is clearly being shared, especially when considering the mid-complexity scores (4-7).

Chapter 04

The Experience Trend: Automating Experiences for Customers, Employees, and More

30% of all automated processes focus on customer or employee experience

Customer experience has the fastest automation growth

“Automation is experience. In many ways, we are building experiences for customers, employees, and more.”

Sridevi Pasumarthi

Head of Biz Tech at Gusto

One could argue that every automation investment is an experience investment, but customer experience (customer support and operations) and employee experience (human resources) are the two categories with experience as their explicit goal. Both are in the top 5 fastest growing departments. Customer support and operations is the highest, doubling year over year. Many of the automated processes within data operations (number two) are underlying customer experiences.

Both HR and customer experience processes have increased in complexity

While the demand for better customer and employee experiences has been increasing, the tech sprawl from chapter 3 is impacting these efforts. HR, notably, became significantly more complex when we look at the year over year data.

more-complex-process-automated-over-time

Chapter 05

The Data Strategy Trend: Building Data Operations for Generative AI

Data operations is experiencing record growth

It is no surprise that data operations is #2 in automation growth, accounting for 32.6% of all automation in 2023. Companies are under enormous pressure to support analytics, advanced analytics, ML, and now generative AI with their data. In addition, the volume of data is continuing to grow at an extraordinary rate, and traditional uses for data are also still in high demand. Companies are still leveraging their data to support business intelligence, advanced analytics and driving business priorities with data.

“Automation is the way to organize data into AI models. Once the model gives the insight, automation inserts it into the business process. I have always seen them [AI and Automation] as entirely interlinked.”

Ted Shelton

Expert Partner at Bain & Company

Data operations is the most automated process in 2024

With generative AI placing new emphasis on data, companies are doubling down on automations to improve data consistency. When we look at all automated processes, data operations is in first place by a wide margin, with 24% of all automated processes. When we look closer at the top sub-processes - data warehousing, data storage, and reverse ETL are all in the top 10.

Data operations are the fastest growing processes in 2024

When we look closely at process growth - we see data strategy as a key theme emerging for 2024. Companies are doubling down on data. They are driving toward alignment with business challenges, and along the way ensuring that their data security, governance, and availability are in order. Ultimately - generative AI is just another stepping stone in the race for companies to derive value from their data. We expect to see this trend continue as generative AI adds new visibility into unstructured data that was previously unavailable to business processes.

Conclusion

The Rise of The New Automation Mindset

The New Automation Mindset describes the first principles that dictate automation strategies in the new AI era. These principles are the growth, process, and scale mindsets:

The process mindset: Also known as systems thinking, this mindset appears when companies automate end to end processes rather than individual tasks.
The growth mindset: Companies with the growth mindset embrace change and challenges in their processes, rather than build rigid, unchanging automations.
The scale mindset: companies with the scale mindset embrace the democratization that was discussed in chapter 2 of this report, allowing both business and IT teams to automate.

In this chapter, we look closely to see where the New Automation Mindset is represented in the data; which data points demonstrate the mindset at work, and which industries have taken the mindset on with the greatest degree of depth.

“The New Automation Mindset shows leaders what it takes to achieve automation in multiple dimensions—process, growth, and scale.”

R Ray Wang

Founder & Chairman at Constellation Research

The new automation mindset is clear in automated processes

companies-automating-more-complex-processes-over-time-and-steady-progress-towards-automating-comlex-processes-over-time

An increase in process complexity suggests that the process mindset is at work. End to end business processes are inherently complex - as the automation subsumes more tasks involved in a process, the complexity captured in this data will naturally increase. Companies that improve their processes over time have the process mindset, but they also demonstrate the growth mindset. The chart on the right that demonstrates the evolution of processes from 6-24 months captures the growth mindset as well.

The top applications applied to automated processes in 2024 include Salesforce, Workbot(c), Jira, Netsuite, SQL Server, and more.

process-savvy-teams-have-higher-automations-persons

lcnc-adoption-higher-in-code-savvy-teams

Appendix 01

Automation Trends by Industry

professional-services-bar-chart-pie-graph

consumer-goods-and-services-pie-chart-bar-chart

Appendix 02

Regional Deep Dive

democratization-maturity-drives-equality-pie-chart

Appendix 03

Research Methodology

This research was conducted using anonymized data sampled over 36 months from 2021 to 2023. The data was collected from 1,055 companies and 82,000 real, automated processes.

Process complexity scores were calculated based on the attributes of the process. Scores of 1-3 are simple, point-to-point integrations with 1-4 steps. They contain no logic, and interconnect simple SaaS applications. Complex processes (4-6) involve conditional rules, logic, looping, data transformations, and cross-reference data. Sometimes they involve batch processing. Highly complex processes involve a combination of SaaS, on-premise, ERP, and enterprise applications. They often contain 30+ steps, with conditional rules, advanced transformation, humans in the loop, and more.