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The Ultimate Guide to Bot as a Service (BaaS) in 2024

The Ultimate Guide to Bot as a Service (BaaS) in 2024The Ultimate Guide to Bot as a Service (BaaS) in 2024

Technology as a service represents the concept of delivering the benefits of technology to a business without on-premise existence of the tool or a long term investment. Common examples include: 

  • Software as a Service (SaaS)
  • Infrastructure as a Service (IaaS)
  • Bot as a Service (BaaS), also known as Robot as a Service (RaaS).,

BasS providers enable businesses to leverage chatbots or RPA bots in a pay-as-you-go manner, without needing to license the bot or train a technical team to manage/maintain it. Please note that BaaS is also used for Backend as a Service.

Bot as a service (BaaS) has been rising in popularity as you can see in the below image (see figure 1). This growth is led by businesses optimizing their digital transformation strategy by maximizing their exposure to emerging tech at minimal complexity. However, using bot as a service  some challenges, for example regarding data privacy and cloud adoption in EU enterprises.

Source: Google

Which bots can be provided as a service?

There are numerous types of bots today, such as:

However, the top bots that are provided as a service are RPA bots and chatbots. RPA bots and chatbots can be provided as a cloud service instead of being maintained by in-house teams. They automate repetitive tasks and facilitate communications with customers without human intervention.

Web scraper as a service

Web data is valuable however websites frequently change their layout which makes it difficult to extract structured data from websites. Web scraping companies identify the data that their clients require and build autonomous web scrapers that they maintain to ensure that their clients have access to fresh data. This is a type of data as a service offering that helps for example hedge funds stay ahead of public markets.

Chatbot as a service

Chatbots are a type of software which enables people to get information from machines in a natural, conversational way using text and voice. Chatbots rely on natural language processing to understand the user’s intent of a conversation and generate responses based on training data or AI capabilities.

Chatbots have numerous applications in

  • Finance:
    • Onboarding clients / employees
    • Improving customer service
    • Transactions
    • Providing financial advice
    • Cross-selling
    • Preventing fraud
  • Healthcare:
    • Provide medical information
    • Schedule medical appointments
    • Collect patient data
    • Handle insurance inquiries
  • Real estate:
    • Generate leads from digital users
    • Build customer profiles
    • Answer questions about properties
    • Answer questions about properties
  • Travel:
    • Search for booking opportunities
    • Manage inquiries
    • Complete reservations
    • Cross-sell

Chatbot as a service, also known as Chatbot SaaS, enables businesses to leverage chatbot capabilities using low-code/no-code cloud platforms with built-in templates for different customer facing tasks such as call center agents or shopping assistants, as well as back office tasks such as employee support.

Some of the companies providing chatbot as a service include:

  • AtBot
  • AI BaaS
  • Fonetic
  • IBM
  • Microsoft Azure

RPA bot as a service

RPA is a type of software which relies on using GUI element and screen scraping as well as other technologies to create specialized agents that can automate repetitive GUI tasks such as reporting, test automation, or SAP processes.

The RPA ecosystem was the fastest-growing segment of the global enterprise software market with a revenue of $846M in 2018, and is expected to reach $11B by 2027.

RPA bot as a service, also known as RPA as a service (RPAaaS), is the process of outsourcing RPA tasks to a service provider which relies on automation, machine learning (ML), and computer vision in order to run repetitive rule-based tasks on the cloud.

Some of the companies providing RPAaaS include:

  • Automation anywhere
  • UiPath
  • BluePrism
  • Robocloud
  • Digital Workforce

To see more, feel free to check out or comprehensive, data driven list of RPA providers.

What are the benefits of implementing Baas?

Bot as a service providers enable businesses to leverage RPA or chatbot capabilities on the cloud, providing the following benefits:

  • No installment or deployment time
  • No licensing, hosting, or infrastructure costs
  • No need to train technical staff to program the bots (BaaS are mostly no-code platforms)
  • Customized permissions to determine bot skills according to user
  • Automated software updates with new version releases
  • Consumption-based or outcome-based pricing options

What are the challenges of BaaS?

Since bot as a service is a cloud-dependent solution, it faces cloud-related challenges such as:

  • Data security: When using cloud services, business data (e.g. security keys, customer data, partner data, employee data) will be stored and processes by a third-party making it prone to breaches, hacks, or credential issues. However, most BaaS providers ensure data privacy via data encryption and by following cybersecurity best practices. Some providers document these by acquiring certificates like ISO 27001 or SOC 2.
  • Cloud adoption: Not all businesses have entirely moved their systems and applications to the cloud; according to a survey, 8% of organizations still have all their data and IT environment on-premise. It is important for businesses who want to leverage BaaS to have all the related data and information already migrated and set up on the cloud.

Nonetheless, BaaS providers can tackle such challenges by integrating data privacy solutions and APIs which facilitate hybrid automation (e.g. on-premise and cloud).

What is the future of BaaS?

It is expected that bot as a service will see a significant rise in popularity in the following years, this will be driven by different factors such as:

  • More businesses are adopting RPA and chatbots to automate everyday tasks
  • Companies preference for SaaS is increasing as measured by increase in valuations of public SaaS companies
  • More funding is raised to accelerate bot improvements and adoption
  • Advances in AI are leading to improved bots which lead to increases in adoption:
    • Natural language processing
    • Sentiment analysis
    • Computer vision

Additionally, customer expectations are also influencing businesses’ digital transformation strategies driving more focus on faster and error-free services which can be facilitated with RPA and chatbots.

Further reading

On RPA:

You can also check out RPA adoption and market size in our article RPA Market Size and Popular Vendors, and explore RPA applications in our data-driven article Top 67 RPA Usecases / Applications/ Examples.

On Chatbots:

Check out statistics and adoption in our article 84 Chatbot /Conversational AI Statistics: Market Size, Adoption, and discover applications and benefits in these two articles:

If you believe your business will benefit from conversational AI, RPA, or web crawlers, don’t hesitate to check our data-driven list of vendors:

And we can guide you through the process:

Find the Right Vendors

This article was drafted by former AIMultiple industry analyst Alamira Jouman Hajjar.

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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