Welcome

As often one of the first interactions, contact centers play an integral role in shaping how customers view and engage with your brand. However, evolving customer expectations and technologies have caused organizations to rethink certain aspects of their contact center. One of the pieces to this puzzle is AI.

How ready is your firm to adopt AI capabilities in your contact center? How do you compare to your peers? Where should you start or focus your AI investment? Find out now with this short assessment.

NICE inContact commissioned Forrester to create the AI readiness self-assessment. The customized results and recommendations will provide insights into your organization’s readiness to adopt AI technologies and available next steps. The assessment should take less than 2 minutes to complete.

Questions

Which of the following, if any, are your company’s goals for the next 12 months? (Select all that apply.)

Grow revenue

Improve customer experience

Improve our products and services

Increase use of data insights in business decisions

Improve our ability to innovate

Don’t know

1 of 8

Questions

How satisfied or dissatisfied are you with your organization’s current contact center tools and capabilities? (Select one.)

Very dissatisfied

Somewhat dissatisfied

Neutral

Somewhat satisfied

Very satisfied

Don’t know

Very dissatisfied

Somewhat dissatisfied

Neutral

Somewhat satisfied

Very satisfied

Don’t know

2 of 8

Questions

What challenges does your company experience in the contact center? (Select all that apply.)

Agents have to use too many diverse applications

Too many data sources

Balancing resources to meet operational goals, such as service levels

Pressure to reduce costs while maintaining service levels

Hiring and retaining agents

Training agents

Outdated or unstable call center technology

Poor visibility into operations (poor reporting)

Lack of integration between call center applications

Lack of integration between call center applications and back office applications

Difficult-to-use call center applications

Difficult/expensive-to-maintain call center systems

Difficulty forecasting and scheduling staffing

None of these; we don’t have any challenges in the contact center

Don’t know

3 of 8

Questions

What are your company’s plans to embed AI in each of the following contact center applications? (Select one per row.)

We define AI in contact center applications as, “Contact center applications that strive to mimic human intelligence through conversation (i.e., natural language understanding and responses), experience, and learning (i.e., machine learning).”

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

Automatic call distribution matching agents to customers through their profiles

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

Quality monitoring

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

Workforce management

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

Agent desktop automation/after-call work (RPA)

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

Customer feedback

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

Chatbots or conversational voice bots

Not interested

Interested but no plans to implement

Planning to implement in the next 12-24 months

Planning to implement within the next 12 months

Already implemented

Expanding or upgrading implementation

Don't know/does not apply

4 of 8

Questions

For each of the areas below, how prepared is your company to support AI in contact center applications? (Select one per row.)

We define AI in contact center applications as, “Contact center applications that strive to mimic human intelligence through conversation (i.e., natural language understanding and responses), experience, and learning (i.e., machine learning).”

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

Strategy – determining the business value and creating the vision

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

Technology – identifying the needed tools

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

Processes – planning a road map, creating a plan for execution

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

Metrics – identifying the key KPIs

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

Talent – sourcing the needed expertise

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

Culture – creating a customer-centric culture

Not prepared at all

Somewhat unprepared

Mostly prepared

Fully prepared

Don’t know/does not apply

5 of 8

Questions

What challenges does your company experience with implementing AI in contact center applications? (Select all that apply.)

We define AI in contact center applications as, “Contact center applications that strive to mimic human intelligence through conversation (i.e., natural language understanding and responses), experience, and learning (i.e., machine learning).”

Lack of expertise to manage or utilize AI in the contact center

Lack of internal resources to groom the data for AI applications

Insufficient data to provide helpful insight for AI applications

Difficulty finding the right AI partner

Difficulty finding the right AI applications

None of these; we don’t have any challenges with implementing AI in contact center applications

6 of 8

Questions

What steps has your company taken to overcome AI implementation challenges? (Select all that apply.)

Hired external support to help us optimize the value of AI tools

Hired AI skilled technical staff to help procure and manage contact center AI applications

Trained internal staff on AI tools and applications

Initiated a series of proof-of-concept projects for AI applications to help expand our experience and knowledge

Utilized the AI application provider training and implementation support services

None of these; we have not taken any steps to overcome our challenges

7 of 8

Questions

Thinking about the next 12 months, what are your company’s investment plans to support AI in the contact center? (Select one.)

We define AI in contact center applications as, “Contact center applications that strive to mimic human intelligence through conversation (i.e., natural language understanding and responses), experience, and learning (i.e., machine learning).”

Increase investment

Keep investment the same

Decrease investment

Don’t know

Increase investment

Keep investment the same

Decrease investment

Don’t know

8 of 8

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Results Overview

While many companies are currently implementing or plan to implement AI-infused applications to augment contact center capabilities, 89% experience a variety of challenges in doing so.

These challenges — lack of internal resources, lack of expertise, difficulty finding the right AI applications or partners — can be detrimental to business performance and prevent firms from maximizing the value their contact center can deliver to their business.

However, the benefits far outweigh the challenges, and 95% of companies are taking steps to overcome AI implementation issues, primarily by seeking more training, expertise, and support from knowledgeable resources.

To ensure AI bolsters contact center capabilities, companies need an effective road map for implementation. See what your next steps look like based on your AI readiness assessment.

Readiness level: AI-Averse

Your score of % makes your organization AI-Averse, like 25% of your peers. There are numerous strategy, technology, process, metrics, talent, and culture changes you can implement to reach higher levels of AI readiness.

Recommendations: What your organizations must do

Assess your customer service strategy and leadership awareness of the prospects and benefits of AI. Mature organizations will go way beyond the call deflection/call reduction approach; you need to determine where your leadership team resides on the maturity spectrum. Cost reductions are generally the entry point, so test to see if your organization is ready to take this step. If not, start the education process for your leadership team.

Tap the experts for education and plan for your first pilot. Building up a level of understanding of AI in the contact center and its benefits is critical to understanding the cultural, process, and people changes needed to embrace the technology. This can be vendors, consultants, and analysts who study the market and can start the initial education and awareness. Preparing for your first pilot will require expertise to map out all the people, process, and technology investments required against a preliminary business case.

Take an “outside-in” approach by developing a deep understanding of customer journeys. AI comes into play at many points in the customer journey, both within self-service and once a contact escalates to an agent. This is somewhat “table stakes” for any customer service organization, but it also helps lay the foundation for AI exploration. The “hot spots” in customer journeys are great prospects to start the journey of integrating AI into your contact center.

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Readiness level: AI-Aware

Your score of % makes your organization AI-Aware, like 59% of your peers. There are numerous strategy, technology, process, metrics, talent, and culture changes you can implement to reach higher levels of AI readiness.

Recommendations: What your organizations must do

Ensure chatbot investments achieve both automation goals and customer satisfaction. Most organizations will start out with the basic business case of deflecting requests for live agent support. So, did your first chatbot pilot achieve its goals for both contact deflection and retaining or boosting customer satisfaction? Make sure the metrics used for evaluating effective customer journeys line up with the AI investments.

Check in with management on strategy, culture, and people changes. During and right after a pilot is the time to revalidate these elements to see if the organization is up to the task of learning and expanding AI more broadly in the entire contact center. At this stage, make the determination as to what level you want to develop internal expertise versus relying on vendors and outside consultants. No matter what, ensure you have enough internal expertise to provide the proper oversight of your AI investments.

Lay out a road map for more expanded use of AI. An AI-enabled agent desktop, more insightful QA, optimized WFM, and enhanced routing are all possible improvements that AI could provide. As AI is highly dependent on feedback data, ensure that each application under consideration has a solid data model in place. Consider the following AI-enabled contact center applications: bots, interaction analytics, predictive analytics, process automation, and authentication.

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Readiness level: AI-Driven

Your score of % makes your organization AI-Driven, like just 16% of your peers. There are numerous strategy, technology, process, metrics, talent, and culture changes you can implement to stay ahead of the pack.

Recommendations: What your organizations must do

Keep checking in on the impact AI is having on your strategy, culture, people, and process. The best practice for any contact center is to always be on the lookout for continuous improvement. As AI has now taken hold broadly in your contact center, ask where the incremental refinements in customer journeys and operations are that can be achieved with deeper tuning and refinement.

If AI is still missing from some applications, explore additional expansion. It’s not just the time at this level of maturity to simply tune the existing applications and their performance, but rather see if there are any other ones you haven’t deployed yet. Consider the following AI-enabled contact center applications: bots, interaction analytics, predictive analytics, process automation, and authentication.

Ensure staff has opportunities to expand their knowledge. It will be years in the future when AI-enabled applications in your contact center mature. As the technology continues to evolve, ensure your staffing model incorporates ongoing training to keep them abreast of industry developments and opportunities.

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View your detailed results

Fill in your details below to receive an explanation of your company’s maturity and thorough recommendations on how you can advance your maturity level.

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Next steps

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Contact NICE inContact

Have questions about how to get started?
1. Call NICE inContact at 1-866-965-7227 to talk to a specialist.
2. Learn more about NICE inContact solutions.

Learn more about

1. The Thought Leadership Study
2. NICE inContact Cxone
3. CXone Automation & Artificial Intelligence
4. NICE inContact Workforce Intelligence

Methodology, Disclaimers and Disclosures

Methodology

In this study, Forrester conducted an online survey of 307 organizations in the US, the UK, and Australia to evaluate adoption of AI in contact centers. Survey participants included decision makers in IT, customer experience, and contact centers who make contact center technology decisions. Questions provided to the participants asked about current contact center tools, plans to adopt AI in contact center applications, and challenges with getting started. Respondents were offered an incentive as a thank you for time spent on the survey. The study began and was completed March 2019.

Disclaimers

Although great care has been taken to ensure the accuracy and completeness of this assessment, NICE inContact and Forrester are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein.

Disclosures

This interactive tool is commissioned by NICE inContact and delivered by Forrester Consulting.

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