Top 5 Roadblocks in the Way of the AI Empowered Community Cloud


Artificial Intelligence (AI) powered technologies are a rage now. AI works in the background, applying software algorithms on big data to replicate a part of human cognitive abilities. A case in point: A YouGov study in the US predicts $2 billion+ online sales generated exclusively by mobile digital assistants.

AI infuses the community cloud with a whole new level of dynamism, enabling enterprises to accomplish amazing things. Business leaders may take better decisions by predicting outcomes. However, key challenges remain, before enterprises can leverage such possibilities to the hilt.

  1. Ensure Seamless Sync

While AI powered community clouds offer a wealth of possibilities, channel partners will not have access to information just because technology enables access.

The possibilities of AI can be explored only when there is effective sync with the internal systems of the company. It requires a culture of transparency and openness to allow the information to pass through the technology.

A key requirement to forge such effective sync is breaking down data and information silos. Data may reside in disparate systems, and ending silos invariably requires a concentrated effort. There is also a need for all concerned stakeholders to integrate their systems, and update data to the community on a real-time basis for the system to work seamlessly.

Trying to break down silos or affect sync might not work through in-house intervention, for the simple reason executives would invariably be overburdened with their core responsibilities. Often, these very executives may be responsible for the silos in the first place. Entrusting the task to an experienced AI implementation partner, who has experience in doing such work, has a large talent pool to actually implement what is required, and who can take an objective view of things, is the way to go.

  1. Make Critical Inputs

Today’s “smart” enterprises get data from billions of data points, on a real-time basis. It is possible to identify potential customer issues through an in-depth analysis of such gathered data, and AI does the task automatically to a large extent. The AI powered community cloud helps decision makers take effective decisions by identifying correlations, similarities, and differences, in half the time. AI goes a step ahead from the earlier generation of big data technologies, by clarifying the context. For instance, while sensors collect sonic data, AI powered cognitive systems identify the user’s taste and preferences from sensor data, and also develop optimized solutions for the user.

However, expecting connected devices to do everything on auto-pilot, leaving business managers free, is farfetched. Effective AI powered automation would require additional support to make sure the AI engine is perfectly placed to generate appropriate responses. As far as business managers are concerned, only the nature of the customer has changed. Hitherto they dealt with end customers directly, with AI powered solutions, connected devices are their new customers. AI powered systems also demand constant assistance to cope with eventualities as they arise. The big advantage is in scale and accuracy. AI powered engines get it accurate, always, and the manager would have to set for the situation just once, rather than re-invent the wheel with each new customer.

Preparing effective data models, and evaluating which data requires human classification is a key challenge that can make or break AI powered systems. Here again, a strategic implementation partner, for whom such tasks are a core focus, and who have specialists for the job, will work wonders.

  1. Have Effective Systems in Place

The community cloud ensures enterprises can access such powerful systems without having to invest in the large amounts of processing power normally required for such tasks. Customer cloud apps that embed AI technologies, for common marketing functions such as forms processing, email marketing, sales forecasting, and customer service, shield organizations from the complexity associated with A. They also improve functionality and performance at the same time. However, the enterprise still needs to be geared up for the improved performance that comes from deploying such AI enabled systems. The enterprise has to ensure the required systems and internal technologies are in place.

A case in point: The AI powered engine may bring in new orders, but it is of little use if the company’s inventory management system is not up to the task of scaling up and have adequate inventory in place, to fulfill the added orders.

A strategic partner, with a wealth of experience beyond them, can easily foresee pain points and help the enterprise prevent possible disasters.

  1. Address the Capability Gap

Even the most advanced enterprises will invariably face a capability gap, or difference between what is to be accomplished and the organizational ability to actually do so.

Effective implementation of AI powered solutions requires experts who know what they are doing. There needs to be an effective coordination with AI experts, and internal business managers who seek added value from the AI implementations. 

Unfortunately, data scientists are in short supply. The talent crunch in machine intelligence might force enterprises to take efforts in developing in-house talent, by investing in training and development. Such interventions are long term, and require extensive investment. More often than not, the best course of action may be to bring in outside experts, by a tie-up with an experienced implementation partner who has the team to do what needs doing.

  1. Reconcile the Cultural Shift

The transformation brought about by AI is not limited to analytics, cognitive computing and machine learning systems in isolation. Artificial intelligence will disrupt businesses in a big way, by forcing businesses to redesign their tasks, job profiles, management practices, and other systems. New technologies, especially automation, will almost certainly eliminate many jobs, and force survivors to approach their tasks in new ways. Such changes may sap the morale of the workforce, and create a reluctance to embrace AI powered technologies. 

The challenge before enterprises is to successfully reconcile the ensuring cultural shock. Employees using AI powered technologies will spend less time performing routine tasks and would focus on work that requires deeper involvement. At the same time, they need to be ready to handle exceptional cases. The onus is on the management to facilitate such a work culture, and keep employees motivated. They need to resolve behavioral and other issues that arise on a proactive basis. The strategic implementation partner helps the enterprise identify potential issues, and prepare a strategy to deal with such issues.

Artificial Intelligence offers a whole new world of possibilities. However, unless the enterprise has their feet on the ground, and takes a realistic view of the situation, they would be guilty of following the hype. What follows the hype, of course, is disillusionment.

Applying AI just for the sake of it does no good. The enterprise needs to have specific goals in mind, and specific use cases. Implementation of AI powered community cloud has to be preceded by an assessment of the potential business and financial value of implementations. In today’s highly charged and competitive business environment, the way to go is to tie any initiative to the direct business value it brings about. A strategic partner allows the enterprise to do all these in the quickest possible time, and gain maximum value for the investment.

If you have any questions that you would like Suyati’s Salesforce team to answer, please write to us on or leave a comment below.

Author : Suyati Salesforce Team Date : 27 Jan 2017